2Flow2SN: Dusty Supernova Cosmology with Photometric Redshifts and Contamination using Neural Simulation-Based Inference

Benjamin M. Boyd; Kaisey S. Mandel; Lisa Kelsey; Madeleine Ginolin; Matthew Grayling; Maximilian Autenrieth; Stephen Thorp

REVIEW

2Flow2SN: Dusty Supernova Cosmology with Photometric Redshifts and Contamination using Neural Simulation-Based Inference

Benjamin M. Boyd, Maximilian Autenrieth, Kaisey S. Mandel, Matthew Grayling, Madeleine Ginolin, Lisa Kelsey, Stephen Thorp

Cosmology and Nongalactic Astrophysics · Submitted 21 Oct 2026 · 239 references

Pith's verdict: A well-constructed modular SBI framework for photometric SN cosmology, but the central claim about amortisation over the Hubble diagram is not tested for the most relevant parameter—M_int0—which could break the second flow.

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CitationBenjamin M. Boyd, Kaisey S. Mandel, Lisa Kelsey, Madeleine Ginolin, Matthew Grayling, Maximilian Autenrieth, Stephen Thorp. "2Flow2SN: Dusty Supernova Cosmology with Photometric Redshifts and Contamination using Neural Simulation-Based Inference." arXiv:2610.30244 (2026). https://pith.science/paper/ORQKXNPE

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Editor's note

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The paper is worth your attention: it extends the FlowSN line to photometric redshifts and contamination with a clean modular design. The key move is a second normalising flow that learns the latent (mu, z) distribution of selected SNe, amortised over the cosmology via a small Gaussian smearing during training. This lets the user swap cosmological models without retraining, which is genuinely useful. The validation on simplified simulations agrees well with an analytical baseline, and the treatment of contamination via Bayesian resampling (Autenrieth et al.) is principled and avoids a misspecified contaminant likelihood. The authors also show scalable inference up to 125k SNe and model comparison via Savage–Dickey ratios at negligible extra cost.

Now the soft spot, and it is load-bearing. The second flow q_phi2 is trained on Δμ = ε_μ ~ N(0, σ_μ²) with σ_μ=0.25. At inference, Δμ includes the term (M_int0 – M_int0,fid), which under the adopted prior can be up to ±2 mag—far outside the training support. The paper never tests this: every simulation fixes M_int0 at the fiducial value. If the flow’s density estimate is unreliable in these low-support regions, the whole inference chain for cosmology and population parameters could be biased. The stress-test note is correct on this point. The authors acknowledge that further training may improve calibration, but they do not address the fundamental coverage of the flow for plausible M_int0 offsets.

Other concerns are minor and mostly acknowledged: Gaussian photo-z errors, exact classification probabilities, and lack of real-world non-Gaussianity and imperfect classifiers. The method’s mathematical structure is sound; the missing test is the one that matters most for the advertised amortisation.

Who gets value from this paper? Researchers in SN SBI and anyone planning a photometric SN analysis pipeline. It deserves peer review because the framework is well motivated and the modular architecture is clever, but the referee should require a dedicated test where M_int0 is varied away from its fiducial value to verify that q_phi2 retains adequate support.

For my own work I would cite this as a promising approach, but I would not rely on it until that test is done. I would maybe bring it to reading group—it’s a good paper to discuss the limits of amortisation.

Referee report

Significance

If the method performs as claimed, it offers a principled and scalable approach to photometric SN Ia cosmology that simultaneously handles selection effects, photometric redshift uncertainties, and non-Ia contamination within a single amortised framework. The ability to reuse the trained normalising flows for different cosmological models and to perform model comparison at negligible additional cost is a practical advantage over methods that require retraining or explicit analytical selection models. The modular Bayesian resampling treatment of contamination is also novel in this context. The demonstration of scaling to 125,000 SNe without retraining suggests readiness for LSST-era datasets. However, the significance is tempered by the reliance on simplified simulations with Gaussian photometric redshift errors and fixed selection functions; the paper acknowledges that further testing on more realistic simulations (e.g., SNANA) and against model misspecification is needed.

Major objections (3)

[Section 2.6.3 and Section 3.1.3] The second normalising flow q_phi2 is trained on Δμ = ε_μ with ε_μ ~ N(0, σ_μ²) and σ_μ=0.25, so during training |Δμ| rarely exceeds ~0.75 mag. At inference, Δμ includes the term M_int0 - M_int0,fid (Eq. 31), which under the adopted prior (Table C1) can be as large as ~2 mag. The flow's density estimate in regions with |Δμ| > 0.75 mag is extrapolating far outside the training distribution. The paper validates the method only on simulations where M_int0 is set exactly to the fiducial value (-19.38) at truth (Tables E1, E2). No test is performed with M_int0 offset from the training value. Since M_int0 is a key parameter of interest, this is a load-bearing gap. The authors should either demonstrate that the flow remains accurate for M_int0 offsets of ±0.5 mag or greater, or discuss why the extrapolation is justified and test it explicitly. Without such validation, the central claim that the framework recovers true population parameters is not fully supported.
[Table E1 and Section 3.1.3] The paper states that for cosmologies C1–C3, biases are below 2σ. However, Table E1 shows that for cosmology C1 with a CMB prior, the posterior median for M_int0 exhibits a bias of 3.9σ (FlowSN2) and 3.5σ (analytical). This contradicts the 'below 2σ' claim. The text should either qualify this statement to exclude M_int0 under the CMB prior, or explain why this bias is considered acceptable. The bias appears to be shared with the analytical solution, which may indicate a prior-volume effect, but it still needs to be discussed transparently.
[Section 3.2.2, Table 1] In the contamination experiments, several population parameters show biases exceeding 2σ when averaged over 25 realisations. For example, in cosmology C1 with Bayesian resampling (SN only), c_int0 has a -2.9σ bias and σ_int has a +2.6σ bias. The paper claims that biases remain within ~2σ, but these values exceed that threshold. While the absolute magnitude of the biases may be small, the statistical significance warrants comment. The authors should either explain why these biases do not undermine the method's validity or discuss potential sources of the discrepancy (e.g., limited simulation realism, flow approximation error).

Minor objections (6)

[Figure 1 caption] The figure caption refers to 'Selection Functions' in the legend but the main text describes selection as a probability (Eq. 52-53); the figure appears to show a hard boundary. Please clarify whether the dashed lines represent the median or the 50% selection contour.
[Equation (27)] The expression for ¯w(z_s) is derived using Bayes' theorem under a fiducial cosmology. The constant P(I_s=1|Θ_SN, ξ_rate=1.5, C=C_1) is said to cancel. It would be helpful to explicitly state that this constant is independent of the parameters being varied (M_int0, γ, etc.) because selection depends only on μ_s and z_s, not on the absolute magnitude zero-point. This is correct but the argument is somewhat implicit.
[Table C1] The training range for σ_μ is not listed; it is given in the text as σ_μ=0.25 (Section 2.6.1). Consider including it in the table for completeness.
[Section 3.1.2] The training sample size is stated as N_train ≈ 25 million selected SNe per survey. Please clarify whether this is the number of SNe after selection or before selection. The phrase 'simulating N_obs ≈ 25 million selected low redshift spectroscopic SNe Ia' suggests post-selection, but this seems very large relative to realistic samples.
[Appendix A] In the derivation of the analytical likelihood, the integration over peculiar velocity is performed analytically. It would be helpful to state explicitly that the peculiar velocity distribution is Gaussian and that the 100/ln(10) factor in the variance of m̂_s arises from the transformation magnitude = -2.5 log10(flux). The current notation is a bit terse.
[General] There are minor typographical issues: in the abstract, 'reanslysis' should be 'reanalysis' (line before references); in Section 2.6.3, 're-parametrised' is misspelled as 're-parametrised' (consistent with British English, but check consistency). Also, 'amortisation' is used throughout but the American spelling 'amortization' appears in a few places (e.g., abstract first mention).

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The paper

The paper claims

FlowSN2 recovers cosmology from photometric SNe under selection and contamination.

The reading

This paper presents FlowSN2, a modular statistical framework that combines hierarchical Bayesian modelling with simulation-based inference to perform cosmological parameter estimation from photometric Type Ia supernova samples. The key innovation is reframing the problem from a regression of distances given spectroscopic redshifts to a joint inference over light curve summaries and photometric redshifts, treating both as data with uncertainties. FlowSN2 uses normalising flows to approximate intractable likelihoods for observed data and latent distances, allowing amortised inference across different cosmologies without retraining. The framework also incorporates a dust model that separates intrinsic SN variations from extrinsic dust effects, and handles non-Ia contamination via a principled Bayesian resampling approach that does not require an explicit contaminant likelihood. In simulated tests, FlowSN2 recovers true cosmological and population parameters, with posteriors matching analytical solutions, and scales to over a hundred thousand supernovae without retraining.

What carries the argument

The two normalising flows: a first flow $q_{\phi_1}$ approximates the intractable likelihood of observed light curve summaries and photometric redshifts given latent distance modulus and redshift, while a second flow $q_{\phi_2}$ learns the latent distance modulus-redshift distribution under selection effects. The second flow is trained with a Gaussian scatter on distance moduli ($\sigma_\mu = 0.25$) to provide support over alternative cosmologies. The flows are trained once on simulations under a fiducial cosmology and can be reused at inference for any cosmology, achieving amortisation. Contamination is handled by modular Bayesian resampling which resamples class labels according to classification scores and averages the pure-Ia posteriors, avoiding an explicit contaminant likelihood.

Extended reading notes

Core claim

FlowSN2 demonstrates that by using two normalising flows—one to learn the distribution of observed light curve summaries and redshifts conditioned on latent distance modulus and redshift, and another to learn the latent distance-redshift distribution under selection—one can achieve amortised inference over the Hubble diagram, enabling parameter estimation for alternative cosmologies (e.g., $w_0 w_a \mathrm{CDM}$) without retraining. The method also successfully propagates photometric classification uncertainty through a modular Bayesian resampling approach that averages posteriors over resampled class allocations. The paper shows that the resulting posteriors are in close agreement with tractable analytical likelihood solutions and pure-Ia baselines, even in the presence of selection effects, photometric redshift uncertainties, and up to 18% non-Ia contamination.

Load-bearing premise

The Gaussian distance modulus smearing ($\sigma_\mu = 0.25$) applied during training is sufficient to provide support over alternative cosmologies at inference time; if the true cosmology or population parameters lie far outside this smeared training distribution, the normalising flow evaluations may become unreliable.

Editorial extensions

If this is right

Photometric SN cosmology can be performed without spectroscopic redshifts, reducing reliance on expensive spectroscopy.
Bayesian model comparison for nested models (e.g., intrinsic mass step vs. dust, evolving dark energy vs. constant) can be done at negligible extra cost using Savage-Dickey ratios.
The framework can scale to LSST and Roman sample sizes (~100,000 SNe) without retraining, enabling robust cosmological constraints.
Selection effects are naturally accounted for through the simulation-based training, removing the need for parametric selection models or binning.
The modular approach to contamination protects inference from misspecified contaminant models while still using all available data.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

The success on simplified simulations with Gaussian photometric redshift uncertainties suggests that extending to non-Gaussian or multimodal redshift estimates (which the authors note is straightforward) could provide a path to handling the most realistic photometric redshift distributions.
Since the normalising flows are trained on pure-Ia simulations and contamination is handled by resampling, the method implicitly assumes that the classification scores are well-calibrated; in practice, calibrating photometric classifiers for high-redshift samples remains an open challenge.
The ability to perform model comparison without retraining could be applied to other nested debates in SN cosmology, such as the presence of a colour-luminosity slope evolution with redshift.
The reliance on a Gaussian smearing ($\sigma_\mu=0.25$) to cover alternative cosmologies may limit support for cosmologies far from the fiducial training point; the authors note this is sufficient for typical prior ranges but it could be tested with broader smearing.

Original abstract

Photometric Type Ia supernova (SN Ia) cosmology in the era of the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) demands statistical frameworks that simultaneously account for selection effects, photometric redshift uncertainties and non-Ia contamination at scale. We present FlowSN2, a modular statistical framework combining hierarchical Bayesian modelling and simulation-based inference (SBI), that reframes photometric SN cosmology from a regression task to a joint inference problem over light curve summaries and photometric redshifts. By employing neural likelihood estimation via normalising flows, FlowSN2 approximates the data distributions of selected objects in a form that can be reused across different cosmological models, achieving amortisation over the Hubble diagram. This amortisation enables inference across alternative cosmological parameterisations, such as $w_0w_a\mathrm{CDM}$, away from the fiducial training cosmology. The framework integrates a standardisation model that disentangles intrinsic SN variations from extrinsic host-galaxy dust effects and adopts a principled Bayesian resampling approach to propagate SN classification uncertainty, without requiring an explicit contaminant likelihood. Across simulated tests spanning five cosmological parameter sets, our framework recovers true cosmological and population parameters, with posteriors in close agreement with both tractable analytical solutions and pure-Ia baselines. Conveniently, the framework enables Bayesian model comparison at negligible additional computational cost, providing a valuable tool for addressing debates surrounding SN standardisation and evolving dark energy. Capable of scaling to over a hundred thousand SNe without retraining, FlowSN2 offers an interpretable and statistically principled solution for cosmological inference with upcoming wide-field photometric surveys.

The compiled record

The paper's own sentences, arranged, kept beside the review and separate from it. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-10-23: 1 request, 7,265 input tokens.

What the abstract itself states, as probabilities: claims first 0.05 · states limitation 0.14 · human participants 0.01 · controlled comparison 0.73 · randomized assignment 0.02 · states quantitative result 0.75 · compares with prior results 0.89 · mentions code or data availability 0.04.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; show every role.

Photometric Type Ia supernova (SN Ia) cosmology in the era of the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) demands statistical frameworks that simultaneously account for selection effects, photometric redshift uncertainties and non-Ia contamination at scale. We present FlowSN2, a modular statistical framework combining hierarchical Bayesian modelling and simulation-based inference (SBI), that reframes photometric SN cosmology from a regression task to a joint inference problem over light curve summaries and photometric redshifts. By employing neural likelihood estimation via normalising flows, FlowSN2 approximates the data distributions of selected objects in a form that can be reused across different cosmological models, achieving amortisation over the Hubble diagram. This amortisation enables inference across alternative cosmological parameterisations, such as $w_0w_a\mathrm{CDM}$, away from the fiducial training cosmology. The framework integrates a standardisation model that disentangles intrinsic SN variations from extrinsic host-galaxy dust effects and adopts a principled Bayesian resampling approach to propagate SN classification uncertainty, without requiring an explicit contaminant likelihood. Across simulated tests spanning five cosmological parameter sets, our framework recovers true cosmological and population parameters, with posteriors in close agreement with both tractable analytical solutions and pure-Ia baselines. Conveniently, the framework enables Bayesian model comparison at negligible additional computational cost, providing a valuable tool for addressing debates surrounding SN standardisation and evolving dark energy. Capable of scaling to over a hundred thousand SNe without retraining, FlowSN2 offers an interpretable and statistically principled solution for cosmological inference with upcoming wide-field photometric surveys.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#	sentence	role	the authors' own work	states the main conclusion	strength
s0	Photometric Type Ia supernova (SN Ia) cosmology in the era of the Vera C.	background 1.00	0.04	0.02	unclear 0.98
s1	Rubin Observatory's Legacy Survey of Space and Time (LSST) demands statistical frameworks that simultaneously account for selection effects, photometric redshift uncertainties and non-Ia contamination at scale.	background 0.94	0.06	0.03	asserted 1.00
s2	We present FlowSN2, a modular statistical framework combining hierarchical Bayesian modelling and simulation-based inference (SBI), that reframes photometric SN cosmology from a regression task to a joint inference problem over light curve summaries and photometric redshifts.	contribution 0.96	0.93	0.23	asserted 1.00
s3	By employing neural likelihood estimation via normalising flows, FlowSN2 approximates the data distributions of selected objects in a form that can be reused across different cosmological models, achieving amortisation over the Hubble diagram.	method 0.98	0.90	0.10	asserted 1.00
s4	This amortisation enables inference across alternative cosmological parameterisations, such as $w_0w_a\mathrm{CDM}$, away from the fiducial training cosmology.	method 0.70	0.73	0.10	asserted 0.97
s5	The framework integrates a standardisation model that disentangles intrinsic SN variations from extrinsic host-galaxy dust effects and adopts a principled Bayesian resampling approach to propagate SN classification uncertainty, without requiring an explicit contaminant likelihood.	method 0.96	0.86	0.13	asserted 1.00
s6	Across simulated tests spanning five cosmological parameter sets, our framework recovers true cosmological and population parameters, with posteriors in close agreement with both tractable analytical solutions and pure-Ia baselines.	result 1.00	0.96	0.42	asserted 1.00
s7	Conveniently, the framework enables Bayesian model comparison at negligible additional computational cost, providing a valuable tool for addressing debates surrounding SN standardisation and evolving dark energy.	interpretation 0.53	0.75	0.15	asserted 0.97
s8	Capable of scaling to over a hundred thousand SNe without retraining, FlowSN2 offers an interpretable and statistically principled solution for cosmological inference with upcoming wide-field photometric surveys.	contribution 0.51	0.76	0.34	asserted 0.93

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from simulation or computation 1.00.

What was examined, and what was not

sources read

arXiv listing abstract v1

not examined

full text
figures and tables
references and citing sentences
relations to other papers

levels run

P abstract

not run

S sections
T body sentences
C citations
R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

Figures

**Figure 1.** Illustration of our simulated surveys used in experiments. Two independent surveys are simulated. We first include a low redshift spectroscopic survey and then a high redshift photometric survey, with larger redshift uncertainties and non-Ia contaminants. The top and right panels are the normalised marginal distributions. Both surveys have their own selection function in observed redshift and apparent magnitude space, shown in the marginals with dashed lines. a given survey’s observational footprint or because the recorded data fails to satisfy the quality cuts. Hereafter, for…

**Figure 2.** The posterior of the global parameters of interest 𝚯 = (𝚯SN, 𝜉rate, 𝑪) conditioned on all the data, framed as a joint inference problem, is 𝑃(𝚯| 𝑫ˆ obs, 𝒁ˆ obs, 𝑰obs) ∝ 𝑃(𝑫ˆ obs, 𝒁ˆ obs| 𝑰obs, 𝚯)𝑃(𝚯| 𝑰obs), (21) where 𝑫ˆ obs = {𝒅ˆ 𝑠 } 𝑁obs SN 𝑠=1 denotes the observed summary statistics for the selected sample and 𝒁ˆ obs = {𝑧ˆ𝑠 } 𝑁obs SN 𝑠=1 denotes the redshift measurements associated with the selected SNe. The selected sample is represented by the indicator vector of ones 𝑰obs = {𝐼𝑠 = 1} 𝑁obs SN 𝑠=1 . The combined data likelihood across all the observed SNe is denoted by 𝑃(𝑫ˆ obs,…

**Figure 3.** Illustration of the FlowSN2 pipeline. The first normalising flow 𝑞 𝝓1 1 learns the observed light curve summary statistics (𝑚ˆ 𝑠 , 𝑐ˆ𝑠 , 𝑥ˆ𝑠 ) and observed redshifts 𝑧ˆ𝑠 distributions under the influence of selection effects, conditioned on the latent redshift 𝑧𝑠 and distance modulus 𝜇𝑠. The second normalising flow 𝑞 𝝓2 2 learns the latent redshift and distance modulus distribution under the influence of selection. The latent redshift distribution under the influence of selection decreases at higher redshifts as Malmquist bias takes effect. The learnt 𝑞 𝝓2 2 represents a noisy…

**Figure 4.** Samples from our trained four-dimensional normalising flow 𝑞 𝝓1 1 corresponding to the photometric redshift survey. We condition on the highest redshift SNe to highlight the maximum impact of selection effects. The distribution of unseen validation data demonstrates that the normalising flow has captured the influence of selection, relative to the full population shown in grey. 3.1.3 SN Ia Only Results Prior to inference, we assess the quality of our learnt 𝑞 𝝓1 1 likelihood approximation by comparing its samples against held-out data distributions as demonstrated in

**Figure 5.** FlowSN2 posteriors on all our cosmological and SN population parameters. These inferences are using a pure-Ia sample with photometric redshifts under the influence of selection. We also show posteriors that use the analytical likelihood solution (defined in Appendix A) for the simplified model and the naive likelihood that does not take selection effects into account. This simulation is from cosmology 𝑪2 showing FlowSN2 is still effective when inferring cosmological parameters away from the fiducial ΛCDM cosmology 𝑪fid = 𝑪1 used in training the normalising flows. The true value for…

**Figure 6.** Mock classification scores for SNe Ia and contaminants in the highredshift photometric sample used in our experiments. These are obtained using the known conditional class probabilities from the simulations. Further experimental details are in Section 3.2.1. rameters, while 𝑪5 are closer to the parameters inferred in the recent DESI results (Adame et al. 2025). For additional constraining power we perform these inferences with a CMB and BAO prior as described in Appendix D. We find that again the FlowSN2 is able to infer the true cosmology under selection effects, with biases less…

**Figure 7.** FlowSN2 𝑤0𝑤𝑎CDM posteriors under the influence of non-Ia contamination. We perform inference with all objects including contaminants to show how they can bias each parameter. We then include inferences using our default approach of modular Bayesian resampling (𝑀 = 5) of the data to account for contamination as described in Section 2.5. For comparison we include inferences on the pure SN Ia subsample using the true labels. Our experiments include a ∼18% post-selection contamination rate. Experimental details can be found in Section 3.2.1. to demonstrate how such model comparisons are…

**Figure 8.** Plot demonstrating the scalability of the FlowSN2 framework inferring cosmological parameters and key SN Ia parameters jointly on increasing sample sizes. These inferences were under the influence of selection effects, with 18% non-Ia contamination rate and with photometric redshifts. The straight lines represent the true parameters in the simulations. parameter at the mass threshold Mstep = 1010 𝑀⊙, following the qualitative picture of Brout & Scolnic (2021). Objects in high-mass hosts are simulated to have a larger 𝜏 (0.098 against 0.068) and a lower 𝑅𝐵 (3.0 against 3.7). The…

Figures reproduced from arXiv:2610.30244 by the authors.

References

Works cited (239)

[1]

Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows , author =. Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics , pages =. 2019 , editor =

View on Pith 2019
[2]

The Pantheon+ analysis: Improving the redshifts and peculiar velocities of Type Ia supernovae used in cosmological analyses. , keywords =. doi:10.1017/pasa.2022.41 , archivePrefix =. 2112.01471 , primaryClass =

View on Pith Pith review arXiv 2022
[3]

James Bradbury and Roy Frostig and Peter Hawkins and Matthew James Johnson and Chris Leary and Dougal Maclaurin and George Necula and Adam Paszke and Jake Vander

View on Pith
[4]

Density estimation by dual ascent of the log-likelihood , author=. Comm. Math. Sci. , volume=. 2010 , publisher=

View on Pith 2010
[5]

Papamakarios, George and Pavlakou, Theo and Murray, Iain , booktitle =. Masked Autoregressive Flow for Density Estimation , url =. 2017 , archivePrefix =

View on Pith 2017
[6]

MADE: Masked Autoencoder for Distribution Estimation , author =. Proceedings of the 32nd International Conference on Machine Learning , pages =. 2015 , editor =

View on Pith 2015
[7]

SIDE-real: Supernova Ia Dust Extinction with truncated marginal neural ratio estimation applied to real data. , keywords =. doi:10.1093/mnras/stae995 , archivePrefix =. 2403.07871 , primaryClass =

View on Pith Pith review arXiv
[8]

The Pantheon+ Analysis: The Full Data Set and Light-curve Release. , keywords =. doi:10.3847/1538-4357/ac8b7a , archivePrefix =. 2112.03863 , primaryClass =

View on Pith Pith review arXiv
[9]

Union through UNITY: Cosmology with 2000 SNe Using a Unified Bayesian Framework. , keywords =. doi:10.3847/1538-4357/adc0a5 , archivePrefix =. 2311.12098 , primaryClass =

View on Pith Pith review arXiv 2000
[11]

Hybrid Monte Carlo , journal =. 1987 , issn =. doi:10.1016/0370-2693(87)91197-X , author =

View on Pith doi:10.1016/0370-2693(87)91197-x 1987
[12]

SimSIMS: Simulation-based Supernova Ia Model Selection with thousands of latent variables. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2311.15650 , archivePrefix =. 2311.15650 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2311.15650
[13]

A family of nonparametric density estimation algorithms , author=. Comm. Pure Applied Math. , volume=. 2013 , publisher=

View on Pith 2013
[14]

The Maximum Mass of Ideal White Dwarfs. , year = 1931, month = jul, volume =. doi:10.1086/143324 , adsurl =

View on Pith doi:10.1086/143324 1931
[15]

A two-parameter luminosity correction for Type IA supernovae. , keywords =

View on Pith
[16]

The Absolute Magnitudes of Type IA Supernovae. , keywords =. doi:10.1086/186970 , adsurl =

View on Pith doi:10.1086/186970
[17]

Hubble Residuals of Nearby Type Ia Supernovae are Correlated with Host Galaxy Masses. , keywords =. doi:10.1088/0004-637X/715/2/743 , archivePrefix =. 0912.0929 , primaryClass =

View on Pith Pith review arXiv
[18]

The dependence of Type Ia Supernovae luminosities on their host galaxies. , keywords =. doi:10.1111/j.1365-2966.2010.16731.x , archivePrefix =. 1003.5119 , primaryClass =

View on Pith Pith review arXiv 2010
[19]

The Effect of Host Galaxies on Type Ia Supernovae in the SDSS-II Supernova Survey. , keywords =. doi:10.1088/0004-637X/722/1/566 , archivePrefix =. 1005.4687 , primaryClass =

View on Pith Pith review arXiv
[20]

Host Galaxy Properties and Hubble Residuals of Type Ia Supernovae from the Nearby Supernova Factory. , keywords =. doi:10.1088/0004-637X/770/2/108 , archivePrefix =. 1304.4720 , primaryClass =

View on Pith Pith review arXiv
[21]

Improved cosmological constraints from a joint analysis of the SDSS-II and SNLS supernova samples. , keywords =. doi:10.1051/0004-6361/201423413 , archivePrefix =. 1401.4064 , primaryClass =

View on Pith Pith review arXiv
[22]

SALT2: using distant supernovae to improve the use of type Ia supernovae as distance indicators. , keywords =. doi:10.1051/0004-6361:20066930 , archivePrefix =. astro-ph/0701828 , primaryClass =

View on Pith Pith review arXiv
[23]

The Supernova Legacy Survey 3-year sample: Type Ia supernovae photometric distances and cosmological constraints. , keywords =. doi:10.1051/0004-6361/201014468 , archivePrefix =. 1010.4743 , primaryClass =

View on Pith Pith review arXiv
[24]

First cosmology results using Type Ia supernova from the Dark Energy Survey: simulations to correct supernova distance biases. , keywords =. doi:10.1093/mnras/stz463 , archivePrefix =. 1811.02379 , primaryClass =

View on Pith Pith review arXiv
[25]

simsurvey: estimating transient discovery rates for the Zwicky transient facility. , keywords =. doi:10.1088/1475-7516/2019/10/005 , archivePrefix =. 1902.03923 , primaryClass =

View on Pith Pith review arXiv 2019
[26]

SNANA: A Public Software Package for Supernova Analysis. , keywords =. doi:10.1086/605984 , archivePrefix =. 0908.4280 , primaryClass =

View on Pith Pith review arXiv
[27]

Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant. , keywords =. doi:10.1086/300499 , archivePrefix =. astro-ph/9805201 , primaryClass =

View on Pith Pith review arXiv
[28]

Hubble Tension: The Evidence of New Physics. Universe , keywords =. doi:10.3390/universe9020094 , archivePrefix =. 2302.05709 , primaryClass =

View on Pith Pith review arXiv
[29]

Discovery of a supernova explosion at half the age of the Universe. , keywords =. doi:10.1038/34124 , archivePrefix =. astro-ph/9712212 , primaryClass =

View on Pith Pith review arXiv
[30]

First Cosmology Results using Type Ia Supernovae from the Dark Energy Survey: Constraints on Cosmological Parameters. , keywords =. doi:10.3847/2041-8213/ab04fa , archivePrefix =. 1811.02374 , primaryClass =

View on Pith Pith review arXiv
[31]

Future Type Ia Supernova Data as Tests of Dark Energy from Modified Friedmann Equations. , keywords =. doi:10.1086/376899 , archivePrefix =. astro-ph/0302064 , primaryClass =

View on Pith Pith review arXiv
[32]

Cosmic Distances Calibrated to 1\. , keywords =. doi:10.3847/2041-8213/abdbaf , archivePrefix =. 2012.08534 , primaryClass =

View on Pith Pith review arXiv 2012
[33]

Planck 2018 results. VI. Cosmological parameters. , keywords =. doi:10.1051/0004-6361/201833910 , archivePrefix =. 1807.06209 , primaryClass =

View on Pith Pith review arXiv 2018
[34]

It's Dust: Solving the Mysteries of the Intrinsic Scatter and Host-galaxy Dependence of Standardized Type Ia Supernova Brightnesses. , keywords =. doi:10.3847/1538-4357/abd69b , archivePrefix =. 2004.10206 , primaryClass =

View on Pith Pith review arXiv 2004
[35]

Sensitivity of the Hubble Constant Determination to Cepheid Calibration. , keywords =. doi:10.3847/1538-4357/ac756e , archivePrefix =. 2105.11461 , primaryClass =

View on Pith Pith review arXiv
[36]

The Hubble Tension Revisited: Additional Local Distance Ladder Uncertainties. , keywords =. doi:10.3847/1538-4357/ac7c19 , archivePrefix =. 2106.09400 , primaryClass =

View on Pith Pith review arXiv
[37]

A BayeSN distance ladder: H _ 0 from a consistent modelling of type ia supernovae from the optical to the near infrared. , keywords =. doi:10.1093/mnras/stad1590 , archivePrefix =. 2211.07657 , primaryClass =

View on Pith Pith review arXiv
[38]

Measurements of the Hubble Constant: Tensions in Perspective. , keywords =. doi:10.3847/1538-4357/ac0e95 , archivePrefix =. 2106.15656 , primaryClass =

View on Pith Pith review arXiv
[39]

A Uniform Type Ia Supernova Distance Ladder with the Zwicky Transient Facility: Absolute Calibration Based on the Tip of the Red Giant Branch Method. , keywords =. doi:10.3847/1538-4357/ac7ceb , archivePrefix =. 2203.04241 , primaryClass =

View on Pith Pith review arXiv
[40]

The Pantheon+ Analysis: Cosmological Constraints. , keywords =. doi:10.3847/1538-4357/ac8e04 , archivePrefix =. 2202.04077 , primaryClass =

View on Pith Pith review arXiv
[41]

The Type Ia Supernova Color-Magnitude Relation and Host Galaxy Dust: A Simple Hierarchical Bayesian Model. , keywords =. doi:10.3847/1538-4357/aa6038 , archivePrefix =. 1609.04470 , primaryClass =

View on Pith Pith review arXiv
[42]

Variational inference for acceleration of SN Ia photometric distance estimation with BayeSN. , keywords =. doi:10.1093/mnras/stae2465 , archivePrefix =. 2405.06013 , primaryClass =

View on Pith Pith review arXiv
[43]

Supernova Limits on the Cosmic Equation of State. , keywords =. doi:10.1086/306495 , archivePrefix =. astro-ph/9806396 , primaryClass =

View on Pith Pith review arXiv
[44]

The Supernova Legacy Survey: measurement of _ M , _ and w from the first year data set. , keywords =. doi:10.1051/0004-6361:20054185 , archivePrefix =. astro-ph/0510447 , primaryClass =

View on Pith Pith review arXiv
[45]

Observational Constraints on the Nature of Dark Energy: First Cosmological Results from the ESSENCE Supernova Survey. , keywords =. doi:10.1086/518642 , archivePrefix =. astro-ph/0701041 , primaryClass =

View on Pith Pith review arXiv
[46]

The Carnegie Supernova Project: First Near-Infrared Hubble Diagram to z -0.5ex 0.7. , keywords =. doi:10.1088/0004-637X/704/2/1036 , archivePrefix =. 0907.4524 , primaryClass =

View on Pith Pith review arXiv
[47]

Improved Cosmological Constraints from New, Old, and Combined Supernova Data Sets. , keywords =. doi:10.1086/589937 , archivePrefix =. 0804.4142 , primaryClass =

View on Pith Pith review arXiv
[48]

Improved constraints on cosmological parameters from Type Ia supernova data. , keywords =. doi:10.1111/j.1365-2966.2011.19584.x , archivePrefix =. 1102.3237 , primaryClass =

View on Pith Pith review arXiv 2011
[49]

UNITY: Confronting Supernova Cosmology's Statistical and Systematic Uncertainties in a Unified Bayesian Framework. , keywords =. doi:10.1088/0004-637X/813/2/137 , archivePrefix =. 1507.01602 , primaryClass =

View on Pith Pith review arXiv
[50]

BAHAMAS: New Analysis of Type Ia Supernovae Reveals Inconsistencies with Standard Cosmology. , keywords =. doi:10.3847/0004-637X/827/1/1 , archivePrefix =. 1510.05954 , primaryClass =

View on Pith Pith review arXiv
[51]

Type Ia Supernova Light-Curve Inference: Hierarchical Bayesian Analysis in the Near-Infrared. , keywords =. doi:10.1088/0004-637X/704/1/629 , archivePrefix =. 0908.0536 , primaryClass =

View on Pith Pith review arXiv
[52]

A hierarchical Bayesian SED model for Type Ia supernovae in the optical to near-infrared. , keywords =. doi:10.1093/mnras/stab3496 , archivePrefix =. 2008.07538 , primaryClass =

View on Pith Pith review arXiv 2008
[53]

Testing the consistency of dust laws in SN Ia host galaxies: a BAYESN examination of Foundation DR1. , keywords =. doi:10.1093/mnras/stab2849 , archivePrefix =. 2102.05678 , primaryClass =

View on Pith Pith review arXiv
[54]

Type Ia Supernova Light Curve Inference: Hierarchical Models in the Optical and Near-infrared. , keywords =. doi:10.1088/0004-637X/731/2/120 , archivePrefix =. 1011.5910 , primaryClass =

View on Pith Pith review arXiv
[55]

The Carnegie Supernova Project: Analysis of the First Sample of Low-Redshift Type-Ia Supernovae. , keywords =. doi:10.1088/0004-6256/139/1/120 , archivePrefix =. 0910.3317 , primaryClass =

View on Pith Pith review arXiv
[56]

Measuring Ejecta Velocity Improves Type Ia Supernova Distances. , keywords =. doi:10.1088/0004-637X/729/1/55 , archivePrefix =. 1011.4517 , primaryClass =

View on Pith Pith review arXiv
[57]

Phillips, M. M. , year=. Near-Infrared Properties of Type Ia Supernovae , volume=. Publications of the Astronomical Society of Australia , publisher=. doi:10.1071/AS11056 , number=

View on Pith doi:10.1071/as11056
[58]

Constraining the SN Ia host galaxy dust law distribution and mass step: hierarchical BAYESN analysis of optical and near-infrared light curves. , keywords =. doi:10.1093/mnras/stac2714 , archivePrefix =. 2209.10552 , primaryClass =

View on Pith Pith review arXiv
[59]

Near-infrared Supernova Ia Distances: Host Galaxy Extinction and Mass-step Corrections Revisited. , keywords =. doi:10.3847/1538-4357/ac2f9e , archivePrefix =. 2105.06236 , primaryClass =

View on Pith Pith review arXiv
[60]

Using rest-frame optical and NIR data from the RAISIN survey to explore the redshift evolution of dust laws in SN Ia host galaxies. , keywords =. doi:10.1093/mnras/stae1111 , archivePrefix =. 2402.18624 , primaryClass =

View on Pith Pith review arXiv
[61]

The Carnegie Supernova Project: Light-curve Fitting with SNooPy. , keywords =. doi:10.1088/0004-6256/141/1/19 , archivePrefix =. 1010.4040 , primaryClass =

View on Pith Pith review arXiv
[62]

The Carnegie Supernova Project: Intrinsic Colors of Type Ia Supernovae. , keywords =. doi:10.1088/0004-637X/789/1/32 , archivePrefix =. 1405.3934 , primaryClass =

View on Pith Pith review arXiv
[63]

The Carnegie Supernova Project: Absolute Calibration and the Hubble Constant. , keywords =. doi:10.3847/1538-4357/aae51c , archivePrefix =. 1809.06381 , primaryClass =

View on Pith Pith review arXiv
[64]

The Carnegie Supernova Project. I. Third Photometry Data Release of Low-redshift Type Ia Supernovae and Other White Dwarf Explosions. , keywords =. doi:10.3847/1538-3881/aa8df0 , archivePrefix =. 1709.05146 , primaryClass =

View on Pith Pith review arXiv
[65]

LSST: From Science Drivers to Reference Design and Anticipated Data Products. , keywords =. doi:10.3847/1538-4357/ab042c , archivePrefix =. 0805.2366 , primaryClass =

View on Pith Pith review arXiv
[66]

Simulations of the WFIRST Supernova Survey and Forecasts of Cosmological Constraints. , keywords =. doi:10.3847/1538-4357/aac08b , archivePrefix =. 1702.01747 , primaryClass =

View on Pith Pith review arXiv
[67]

Carnegie Supernova Project-II: Extending the Near-infrared Hubble Diagram for Type Ia Supernovae to z 0.1. , keywords =. doi:10.1088/1538-3873/aae8bd , archivePrefix =. 1810.09252 , primaryClass =

View on Pith Pith review arXiv
[68]

The Young Supernova Experiment: Survey Goals, Overview, and Operations. , keywords =. doi:10.3847/1538-4357/abd7f5 , archivePrefix =. 2010.09724 , primaryClass =

View on Pith Pith review arXiv 2010
[69]

The Zwicky Transient Facility Type Ia supernova survey: first data release and results. , keywords =. doi:10.1093/mnras/stab3093 , archivePrefix =. 2110.07256 , primaryClass =

View on Pith Pith review arXiv
[70]

Carnegie Supernova Project-II: The Near-infrared Spectroscopy Program. , keywords =. doi:10.1088/1538-3873/aae961 , archivePrefix =. 1810.08213 , primaryClass =

View on Pith Pith review arXiv
[71]

Spectroscopy of Type Ia Supernovae by the Carnegie Supernova Project. , keywords =. doi:10.1088/0004-637X/773/1/53 , archivePrefix =. 1305.6997 , primaryClass =

View on Pith Pith review arXiv
[72]

The Spectroscopic Diversity of Type Ia Supernovae. , keywords =. doi:10.1088/0004-6256/143/5/126 , archivePrefix =. 1203.4832 , primaryClass =

View on Pith Pith review arXiv
[73]

Abundance stratification in Type Ia supernovae - IV. The luminous, peculiar SN 1991T. , keywords =. doi:10.1093/mnras/stu1777 , archivePrefix =. 1409.0116 , primaryClass =

View on Pith Pith review arXiv
[74]

Photometric and Spectroscopic Properties of Type Ia Supernova 2018oh with Early Excess Emission from the Kepler 2 Observations. , keywords =. doi:10.3847/1538-4357/aaec74 , archivePrefix =. 1811.10056 , primaryClass =

View on Pith Pith review arXiv
[75]

Multi-Object Spectroscopy with Optical Fibres. Very Large Telescopes and their Instrumentation, Vol. 2 , year = 1988, series =

View on Pith 1988
[76]

APERO: A PipelinE to Reduce Observations-Demonstration with SPIRou. , keywords =. doi:10.1088/1538-3873/ac9e74 , archivePrefix =. 2211.01358 , primaryClass =

View on Pith Pith review arXiv
[77]

On the Compared Accuracy and Reliability of Spectroscopic and Photometric Redshift Measurements. , keywords =. doi:10.1086/321777 , archivePrefix =. astro-ph/0007447 , primaryClass =

View on Pith Pith review arXiv
[78]

K-Corrections and Spectral Templates of Type Ia Supernovae. , keywords =. doi:10.1086/518232 , archivePrefix =. astro-ph/0703529 , primaryClass =

View on Pith Pith review arXiv
[79]

Carnegie Supernova Project. II. Near-infrared Spectral Diversity and Template of Type Ia Supernovae. , keywords =. doi:10.3847/1538-4357/acc100 , archivePrefix =. 2211.05998 , primaryClass =

View on Pith Pith review arXiv
[80]

Spectroscopic diversity of Type Ia supernovae , author =

View on Pith
[81]

Rasmussen, Carl Edward and Williams, Christopher K. I. , title = ". 2005 , month =. doi:10.7551/mitpress/3206.001.0001 , url =

View on Pith doi:10.7551/mitpress/3206.001.0001 2005
[82]

Spectrophotometric templates for core-collapse supernovae and their application in simulations of time-domain surveys. , keywords =. doi:10.1093/mnras/stz2448 , archivePrefix =. 1908.05228 , primaryClass =

View on Pith Pith review arXiv 1908
[83]

What can Gaussian processes really tell us about supernova light curves? Consequences for Type II(b) morphologies and genealogies. , keywords =. doi:10.1093/mnras/stac3523 , archivePrefix =. 2206.14816 , primaryClass =

View on Pith Pith review arXiv
[84]

Investigating the diversity of Type Ia supernova spectra with the open-source relational data base KAEPORA. , keywords =. doi:10.1093/mnras/stz1209 , archivePrefix =. 1905.02204 , primaryClass =

View on Pith Pith review arXiv 1905
[85]

A possible distance bias for type Ia supernovae with different ejecta velocities. , keywords =. doi:10.1093/mnras/staa577 , archivePrefix =. 2002.09490 , primaryClass =

View on Pith Pith review arXiv 2002
[86]

Berkeley Supernova Ia Program - I. Observations, data reduction and spectroscopic sample of 582 low-redshift Type Ia supernovae. , keywords =. doi:10.1111/j.1365-2966.2012.21270.x , archivePrefix =. 1202.2128 , primaryClass =

View on Pith Pith review arXiv 2012
[87]

Properties of Type Ia Supernova , author =

View on Pith
[88]

Velocity Evolution and the Intrinsic Color of Type Ia Supernovae. , keywords =. doi:10.1088/0004-637X/742/2/89 , archivePrefix =. 1107.3555 , primaryClass =

View on Pith Pith review arXiv
[89]

Optical and infrared observations of SN 2002dj: some possible common properties of fast-expanding Type Ia supernovae. , keywords =. doi:10.1111/j.1365-2966.2008.13434.x , archivePrefix =. 0805.1089 , primaryClass =

View on Pith Pith review arXiv 2008
[90]

Direct Analysis of Spectra of the Peculiar Type Ia Supernova 2000cx. , keywords =. doi:10.1086/382950 , archivePrefix =. astro-ph/0401324 , primaryClass =

View on Pith Pith review arXiv
[91]

Near-infrared light curves of Type Ia supernovae: studying properties of the second maximum. , keywords =. doi:10.1093/mnras/stu2716 , archivePrefix =. 1502.00568 , primaryClass =

View on Pith Pith review arXiv
[92]

Subpercent Photometry: Faint DA White Dwarf Spectrophotometric Standards for Astrophysical Observatories. , keywords =. doi:10.3847/1538-4365/ab0557 , archivePrefix =. 1811.12534 , primaryClass =

View on Pith Pith review arXiv
[93]

Systematic Uncertainties Associated with the Cosmological Analysis of the First Pan-STARRS1 Type Ia Supernova Sample. , keywords =. doi:10.1088/0004-637X/795/1/45 , archivePrefix =. 1310.3824 , primaryClass =

View on Pith Pith review arXiv
[94]

Techniques and Review of Absolute Flux Calibration from the Ultraviolet to the Mid-Infrared. , keywords =. doi:10.1086/677655 , archivePrefix =. 1406.1707 , primaryClass =

View on Pith Pith review arXiv
[95]

Hubble Space Telescope CALSPEC Flux Standards: Sirius (and Vega). , keywords =. doi:10.1088/0004-6256/147/6/127 , adsurl =

View on Pith doi:10.1088/0004-6256/147/6/127
[96]

The No-U-Turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo. , author=. J. Mach. Learn. Res. , volume=

View on Pith
[97]

Probabilistic programming in Python using PyMC3 , author=. PeerJ Computer Science , volume=. 2016 , publisher=

View on Pith 2016
[98]

Non-LTE Line-blanketed Model Atmospheres of Hot Stars. I. Hybrid Complete Linearization/Accelerated Lambda Iteration Method. , keywords =. doi:10.1086/175226 , adsurl =

View on Pith doi:10.1086/175226
[99]

All-Sky Faint DA White Dwarf Spectrophotometric Standards for Astrophysical Observatories: The Complete Sample. arXiv e-prints , keywords =. doi:10.48550/arXiv.2305.07563 , archivePrefix =. 2305.07563 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2305.07563
[100]

Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro. ArXiv e-prints , keywords =. doi:10.48550/arXiv.1912.11554 , archivePrefix =. 1912.11554 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.1912.11554 1912
[101]

Measuring the Hubble constant with Type Ia supernovae as near-infrared standard candles. , keywords =. doi:10.1051/0004-6361/201731501 , archivePrefix =. 1707.00715 , primaryClass =

View on Pith Pith review arXiv
[102]

Binaries and Supernovae of Type I. , year = 1973, month = dec, volume =. doi:10.1086/152565 , adsurl =

View on Pith doi:10.1086/152565 1973
[103]

The evolution of low-mass close binaries influenced by the radiation of gravitational waves and by a magnetic stellar wind. , keywords =. doi:10.1086/162455 , adsurl =

View on Pith doi:10.1086/162455
[104]

Paolo A. Mazzali and Friedrich K. Röpke and Stefano Benetti and Wolfgang Hillebrandt , title =. Science , volume =. 2007 , doi =. https://www.science.org/doi/pdf/10.1126/science.1136259 , abstract =

View on Pith doi:10.1126/science.1136259 2007
[105]

POLYCHORD: next-generation nested sampling. , keywords =. doi:10.1093/mnras/stv1911 , archivePrefix =. 1506.00171 , primaryClass =

View on Pith Pith review arXiv
[106]

Evidence Networks: simple losses for fast, amortized, neural Bayesian model comparison. Machine Learning: Sci.\ Technol. , keywords =. doi:10.1088/2632-2153/ad1a4d , archivePrefix =. 2305.11241 , primaryClass =

View on Pith Pith review arXiv
[107]

Clarifying the Hubble constant tension with a Bayesian hierarchical model of the local distance ladder. , keywords =. doi:10.1093/mnras/sty418 , archivePrefix =. 1707.00007 , primaryClass =

View on Pith Pith review arXiv
[108]

The Dust Attenuation Law in Galaxies. , keywords =. doi:10.1146/annurev-astro-032620-021933 , archivePrefix =. 2001.03181 , primaryClass =

View on Pith Pith review arXiv 2001
[109]

Draine, B.T. , title =. Annual Review of Astronomy and Astrophysics , volume =. 2003 , doi =. https://doi.org/10.1146/annurev.astro.41.011802.094840 , abstract =

View on Pith Pith review doi:10.1146/annurev.astro.41.011802.094840 2003
[110]

An Analysis of the Shapes of Interstellar Extinction Curves. V. The IR-through-UV Curve Morphology. , keywords =. doi:10.1086/518158 , archivePrefix =. 0705.0154 , primaryClass =

View on Pith Pith review arXiv
[111]

An Analysis of the Shapes of Interstellar Extinction Curves. VI. The Near-IR Extinction Law. , keywords =. doi:10.1088/0004-637X/699/2/1209 , archivePrefix =. 0905.0133 , primaryClass =

View on Pith Pith review arXiv
[112]

The effects of varying colour-luminosity relations on Type Ia supernova science. , keywords =. doi:10.1093/mnras/stab2802 , archivePrefix =. 2009.13230 , primaryClass =

View on Pith Pith review arXiv 2009
[113]

Relative Intrinsic Scatter in Hierarchical Type Ia Supernova Sibling Analyses: Application to SNe 2021hpr, 1997bq, and 2008fv in NGC 3147. , keywords =. doi:10.3847/1538-4357/acf7bb , archivePrefix =. 2209.10558 , primaryClass =

View on Pith Pith review arXiv
[114]

On some relations in stellar statistics. Medd.\ Lunds Astron.\ Obser.\ Serie I , year = 1922, month = mar, volume =

View on Pith 1922
[115]

Correcting Type Ia Supernova Distances for Selection Biases and Contamination in Photometrically Identified Samples. , keywords =. doi:10.3847/1538-4357/836/1/56 , archivePrefix =. 1610.04677 , primaryClass =

View on Pith Pith review arXiv
[116]

A Bayesian approach to truncated data sets: An application to Malmquist bias in Supernova Cosmology. ArXiv e-prints , keywords =. doi:10.48550/arXiv.1804.02474 , archivePrefix =. 1804.02474 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.1804.02474
[117]

Mixture density networks , author=. 1994 , number =

View on Pith 1994
[118]

Variational Inference with Normalizing Flows , author =. Proceedings of the 32nd International Conference on Machine Learning , pages =. 2015 , editor =

View on Pith 2015
[119]

Hermans, Joeri and Begy, Volodimir and Louppe, Gilles , booktitle =. Likelihood-free. 2020 , editor =

View on Pith 2020
[120]

SICRET: Supernova Ia Cosmology with truncated marginal neural Ratio EsTimation. , keywords =. doi:10.1093/mnras/stac3785 , archivePrefix =. 2209.06733 , primaryClass =

View on Pith Pith review arXiv
[121]

Amortized bayesian inference for supernovae in the era of the vera rubin observatory using normalizing flows , author=. arXiv preprint arXiv:2211.04480 , year=

View on Pith Pith review arXiv
[122]

Measurements of and from 42 High-Redshift Supernovae. , keywords =. doi:10.1086/307221 , adsurl =

View on Pith Pith review doi:10.1086/307221
[123]

SN 2022ann: a Type Icn supernova from a dwarf galaxy that reveals helium in its circumstellar environment. , keywords =. doi:10.1093/mnras/stad1433 , archivePrefix =. 2211.05134 , primaryClass =

View on Pith arXiv
[124]

Fast likelihood-free cosmology with neural density estimators and active learning. , keywords =. doi:10.1093/mnras/stz1960 , archivePrefix =. 1903.00007 , primaryClass =

View on Pith Pith review arXiv 1903
[125]

George Papamakarios and Eric Nalisnick and Danilo Jimenez Rezende and Shakir Mohamed and Balaji Lakshminarayanan , title =. J.\ Machine Learning Res. , year =

View on Pith
[126]

Eli Bingham and Jonathan P. Chen and Martin Jankowiak and Fritz Obermeyer and Neeraj Pradhan and Theofanis Karaletsos and Rohit Singh and Paul A. Szerlip and Paul Horsfall and Noah D. Goodman , title =. J. Machine Learning Res. , volume =. 2019 , url =

View on Pith 2019
[127]

The Effect of Peculiar Velocities on Supernova Cosmology. , keywords =. doi:10.1088/0004-637X/741/1/67 , archivePrefix =. 1012.2912 , primaryClass =

View on Pith Pith review arXiv
[128]

Redshift evolution of the underlying type Ia supernova stretch distribution. , keywords =. doi:10.1051/0004-6361/202038447 , archivePrefix =. 2005.09441 , primaryClass =

View on Pith Pith review arXiv 2005
[129]

ZTF SN Ia DR2: The diversity and relative rates of the thermonuclear supernova population. , keywords =. doi:10.1051/0004-6361/202451852 , archivePrefix =. 2406.01434 , primaryClass =

View on Pith arXiv
[130]

ZTF SN Ia DR2: Environmental dependencies of stretch and luminosity for a volume-limited sample of 1000 type Ia supernovae. , keywords =. doi:10.1051/0004-6361/202450378 , archivePrefix =. 2405.20965 , primaryClass =

View on Pith Pith review arXiv
[131]

ZTF SN Ia DR2: Colour standardisation of type Ia supernovae and its dependence on the environment. , keywords =. doi:10.1051/0004-6361/202450943 , archivePrefix =. 2406.02072 , primaryClass =

View on Pith Pith review arXiv
[132]

The Pantheon+ Analysis: Forward Modeling the Dust and Intrinsic Color Distributions of Type Ia Supernovae, and Quantifying Their Impact on Cosmological Inferences. , keywords =. doi:10.3847/1538-4357/aca273 , archivePrefix =. 2112.04456 , primaryClass =

View on Pith Pith review arXiv
[133]

Scalable hierarchical BayeSN inference: investigating dependence of SN Ia host galaxy dust properties on stellar mass and redshift. , keywords =. doi:10.1093/mnras/stae1202 , archivePrefix =. 2401.08755 , primaryClass =

View on Pith Pith review arXiv
[134]

SALT3: An Improved Type Ia Supernova Model for Measuring Cosmic Distances. , keywords =. doi:10.3847/1538-4357/ac30d8 , archivePrefix =. 2104.07795 , primaryClass =

View on Pith Pith review arXiv
[135]

Accounting for Selection Effects in Supernova Cosmology with Simulation-Based Inference and Hierarchical Bayesian Modelling. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2407.15923 , archivePrefix =. 2407.15923 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2407.15923
[136]

STAR NRE: solving supernova selection effects with set-based truncated auto-regressive neural ratio estimation. , keywords =. doi:10.1088/1475-7516/2025/07/031 , archivePrefix =. 2409.03837 , primaryClass =

View on Pith Pith review arXiv 2025
[137]

Andrew Gelman and Donald B. Rubin , title =. Statistical Sci. , number =. 1992 , doi =

View on Pith 1992
[138]

Rank-normalization, folding, and localization: An improved R-hat for assessing convergence of MCMC (with Discussion). Bayesian Analysis , keywords =. doi:10.1214/20-BA1221 , archivePrefix =. 1903.08008 , primaryClass =

View on Pith Pith review arXiv 1903
[139]

Optimizing The Integrator Step Size for Hamiltonian Monte Carlo. ArXiv e-prints , keywords =. doi:10.48550/arXiv.1411.6669 , archivePrefix =. 1411.6669 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.1411.6669
[140]

A Conceptual Introduction to Hamiltonian Monte Carlo. ArXiv e-prints , keywords =. doi:10.48550/arXiv.1701.02434 , archivePrefix =. 1701.02434 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.1701.02434
[141]

Matthew D. Hoffman and Andrew Gelman , title =. Journal of Machine Learning Research , year =

View on Pith
[142]

Reassessing the ZTF Volume-limited Type Ia Supernova Sample and Its Implications for Continuous, Dust-dependent Models of Intrinsic Scatter. , keywords =. doi:10.3847/1538-4357/ae122d , archivePrefix =. 2505.04686 , primaryClass =

View on Pith Pith review arXiv
[143]

Binning is Sinning: Redemption for Hubble Diagram Using Photometrically Classified Type Ia Supernovae. , keywords =. doi:10.3847/2041-8213/ace34d , archivePrefix =. 2306.05819 , primaryClass =

View on Pith Pith review arXiv
[144]

Binning is Sinning (Supernova Version): The Impact of Self-calibration in Cosmological Analyses with Type Ia Supernovae. , keywords =. doi:10.3847/2041-8213/abf4db , archivePrefix =. 2012.05900 , primaryClass =

View on Pith Pith review arXiv 2012
[145]

CIGaRS I: combined simulation-based inference from type Ia supernovae and host photometry. Nature Astronomy , keywords =. doi:10.1038/s41550-026-02842-5 , archivePrefix =. 2508.15899 , primaryClass =

View on Pith Pith review arXiv
[146]

Hierarchical Simulation-Based Inference of Supernova Power Sources and their Physical Properties. arXiv e-prints , keywords =. doi:10.48550/arXiv.2510.14202 , archivePrefix =. 2510.14202 , primaryClass =

View on Pith doi:10.48550/arxiv.2510.14202
[147]

Hierarchical Neural Simulation-Based Inference Over Event Ensembles , author=. Transactions on Machine Learning Research , issn=. 2024 , url=

View on Pith 2024
[148]

Improved Distances to Type Ia Supernovae with Multicolor Light-Curve Shapes: MLCS2k2. , keywords =. doi:10.1086/512054 , archivePrefix =. astro-ph/0612666 , primaryClass =

View on Pith Pith review arXiv
[149]

Distance measures in cosmology. ArXiv e-prints , keywords =. doi:10.48550/arXiv.astro-ph/9905116 , archivePrefix =. astro-ph/9905116 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.astro-ph/9905116
[150]

A Measurement of the Rate of Type Ia Supernovae at Redshift z 0.1 from the First Season of the SDSS-II Supernova Survey. , keywords =. doi:10.1086/587733 , archivePrefix =. 0801.3297 , primaryClass =

View on Pith Pith review arXiv
[151]

DAmodel: hierarchical Bayesian modelling of DA white dwarfs for spectrophotometric calibration. , keywords =. doi:10.1093/mnras/staf629 , archivePrefix =. 2412.08809 , primaryClass =

View on Pith Pith review arXiv
[152]

Type Ia Supernova Colors and Ejecta Velocities: Hierarchical Bayesian Regression with Non-Gaussian Distributions. , keywords =. doi:10.1088/0004-637X/797/2/75 , archivePrefix =. 1402.7079 , primaryClass =

View on Pith Pith review arXiv
[153]

The subtle statistics of the distance ladder: On the distance prior and selection effects. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2511.03394 , archivePrefix =. 2511.03394 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2511.03394
[154]

4MOST: Project overview and information for the First Call for Proposals. The Messenger , keywords =. doi:10.18727/0722-6691/5117 , archivePrefix =. 1903.02464 , primaryClass =

View on Pith Pith review arXiv 1903
[155]

TiDES: The 4MOST Time Domain Extragalactic Survey. , keywords =. doi:10.3847/1538-4357/adff4e , archivePrefix =. 2501.16311 , primaryClass =

View on Pith Pith review arXiv
[156]

Using Host Galaxy Photometric Redshifts to Improve Cosmological Constraints with Type Ia Supernovae in the LSST Era. , keywords =. doi:10.3847/1538-4357/acb057 , archivePrefix =. 2210.07560 , primaryClass =

View on Pith Pith review arXiv
[157]

Models and Simulations for the Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC). , keywords =. doi:10.1088/1538-3873/ab26f1 , archivePrefix =. 1903.11756 , primaryClass =

View on Pith Pith review arXiv 1903
[158]

Measuring Type Ia Supernova Populations of Stretch and Color and Predicting Distance Biases. , keywords =. doi:10.3847/2041-8205/822/2/L35 , archivePrefix =. 1603.01559 , primaryClass =

View on Pith Pith review arXiv
[159]

Correcting for the Effects of Interstellar Extinction. , keywords =. doi:10.1086/316293 , archivePrefix =. astro-ph/9809387 , primaryClass =

View on Pith Pith review arXiv
[160]

Measuring Reddening with Sloan Digital Sky Survey Stellar Spectra and Recalibrating SFD. , keywords =. doi:10.1088/0004-637X/737/2/103 , archivePrefix =. 1012.4804 , primaryClass =

View on Pith Pith review arXiv
[161]

Five-Year Wilkinson Microwave Anisotropy Probe Observations: Cosmological Interpretation. , keywords =. doi:10.1088/0067-0049/180/2/330 , archivePrefix =. 0803.0547 , primaryClass =

View on Pith Pith review arXiv
[162]

A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2110.06581 , archivePrefix =. 2110.06581 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2110.06581
[163]

The Dark Energy Survey: Cosmology Results with 1500 New High-redshift Type Ia Supernovae Using the Full 5 yr Data Set. , keywords =. doi:10.3847/2041-8213/ad6f9f , archivePrefix =. 2401.02929 , primaryClass =

View on Pith Pith review arXiv
[164]

Evolving dark energy or supernovae systematics?. , keywords =. doi:10.1093/mnras/staf301 , archivePrefix =. 2408.07175 , primaryClass =

View on Pith Pith review arXiv
[165]

The axis of systematic bias in SN Ia cosmology and implications for DESI 2024 results. , keywords =. doi:10.1093/mnras/staf779 , archivePrefix =. 2409.18668 , primaryClass =

View on Pith Pith review arXiv 2024
[166]

Strong progenitor age bias in supernova cosmology ─ II. Alignment with DESI BAO and signs of a non-accelerating universe. , keywords =. doi:10.1093/mnras/staf1685 , archivePrefix =. 2510.13121 , primaryClass =

View on Pith arXiv
[167]

Still Accelerating: Type Ia supernova cosmology is robust to host galaxy age evolution. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2601.13785 , archivePrefix =. 2601.13785 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2601.13785
[168]

SNIa Cosmology Analysis Results from Simulated LSST Images: From Difference Imaging to Constraints on Dark Energy. , keywords =. doi:10.3847/1538-4357/ac7a37 , archivePrefix =. 2111.06858 , primaryClass =

View on Pith Pith review arXiv
[169]

ZTF SN Ia DR2: Improved SN Ia colors through expanded dimensionality with SALT3+. , keywords =. doi:10.1051/0004-6361/202452578 , archivePrefix =. 2502.09713 , primaryClass =

View on Pith Pith review arXiv
[170]

A revised SALT2 surface for fitting Type Ia supernova light curves. , keywords =. doi:10.1093/mnras/stab962 , archivePrefix =. 2104.00172 , primaryClass =

View on Pith Pith review arXiv
[171]

ZTF SN Ia DR2: Evidence of changing dust distribution with redshift using type Ia supernovae. , keywords =. doi:10.1051/0004-6361/202450391 , archivePrefix =. 2406.06215 , primaryClass =

View on Pith Pith review arXiv
[172]

Space Distribution and Luminosity Functions of Quasi-Stellar Radio Sources. , year = 1968, month = feb, volume =. doi:10.1086/149446 , adsurl =

View on Pith doi:10.1086/149446 1968
[173]

Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog. , keywords =. doi:10.3847/2041-8213/abe949 , archivePrefix =. 2010.14533 , primaryClass =

View on Pith Pith review arXiv 2010
[174]

Stellar masses and star formation histories for 10 ^ 5 galaxies from the Sloan Digital Sky Survey. , keywords =. doi:10.1046/j.1365-8711.2003.06291.x , archivePrefix =. astro-ph/0204055 , primaryClass =

View on Pith Pith review arXiv 2003
[175]

Occurrence Rates of Planets Orbiting FGK Stars: Combining Kepler DR25, Gaia DR2, and Bayesian Inference. , keywords =. doi:10.3847/1538-3881/ab31ab , archivePrefix =. 1902.01417 , primaryClass =

View on Pith Pith review arXiv 1902
[176]

Prevalence of Earth-size planets orbiting Sun-like stars. Proc.\ Natl.\ Acad.\ Sci. , keywords =. doi:10.1073/pnas.1319909110 , archivePrefix =. 1311.6806 , primaryClass =

View on Pith Pith review arXiv
[177]

The ejected mass distribution of Type Ia supernovae: a significant rate of non-Chandrasekhar-mass progenitors. , keywords =. doi:10.1093/mnras/stu1808 , archivePrefix =. 1408.6601 , primaryClass =

View on Pith Pith review arXiv
[178]

Lightcurve Modelling of 2,205 ZTF DR2 Type -0.5ex Supernovae: Implications for SN Ia Physics and Cosmology. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2602.02677 , archivePrefix =. 2602.02677 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2602.02677
[179]

Banana Split: Improved Cosmological Constraints with Two Light-Curve-Shape and Color Populations Using Union3.1+UNITY1.8. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2601.19854 , archivePrefix =. 2601.19854 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2601.19854
[180]

Union3.1: Self-consistent Measurements of Host Galaxy Properties for 2000 Type Ia Supernovae. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2601.19424 , archivePrefix =. 2601.19424 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2601.19424 2000
[181]

The frontier of simulation-based inference. Proc.\ Natl.\ Acad.\ Sci. , keywords =. doi:10.1073/pnas.1912789117 , archivePrefix =. 1911.01429 , primaryClass =

View on Pith Pith review arXiv 1911
[182]

Data-driven dust inference at mid-to-high Galactic latitudes using probabilistic machine learning. , keywords =. doi:10.1093/mnras/staf2147 , archivePrefix =. 2508.05781 , primaryClass =

View on Pith arXiv
[183]

Misspecification-robust amortised simulation-based inference using variational methods. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2509.05724 , archivePrefix =. 2509.05724 , primaryClass =

View on Pith doi:10.48550/arxiv.2509.05724
[184]

DESI 2024 VI: cosmological constraints from the measurements of baryon acoustic oscillations. , keywords =. doi:10.1088/1475-7516/2025/02/021 , archivePrefix =. 2404.03002 , primaryClass =

View on Pith Pith review arXiv 2024
[185]

Comparing the DES-SN5YR and Pantheon+ SN cosmology analyses: investigation based on 'evolving dark energy or supernovae systematics'?. , keywords =. doi:10.1093/mnras/staf943 , archivePrefix =. 2501.06664 , primaryClass =

View on Pith Pith review arXiv
[186]

Selection Functions in Astronomical Data Modeling, with the Space Density of White Dwarfs as a Worked Example. , keywords =. doi:10.3847/1538-3881/ac0c13 , archivePrefix =. 2106.07653 , primaryClass =

View on Pith Pith review arXiv
[187]

Improved weak lensing photometric redshift calibration via StratLearn and hierarchical modelling. , keywords =. doi:10.1093/mnras/stae2243 , archivePrefix =. 2401.04687 , primaryClass =

View on Pith Pith review arXiv
[188]

A Fully Photometric Approach to Type Ia Supernova Cosmology in the LSST Era: Host-galaxy Redshifts and Supernova Classification. , keywords =. doi:10.3847/1538-4357/ae7a41 , archivePrefix =. 2512.06319 , primaryClass =

View on Pith Pith review arXiv
[189]

Environmental Dependence of Type Ia Supernovae in Low-redshift Galaxy Clusters. , keywords =. doi:10.3847/1538-4357/ad0e0f , archivePrefix =. 2306.01088 , primaryClass =

View on Pith Pith review arXiv
[190]

FlowJAX: Distributions and Normalizing Flows in Jax , author =. 2024 , doi =

View on Pith 2024
[191]

Colm Talbot and Amanda Farah and Shanika Galaudage and Jacob Golomb and Hui Tong , title =. Journal of Open Source Software , doi =. 2025 , publisher =

View on Pith 2025
[192]

JAX-COSMO: An End-to-End Differentiable and GPU Accelerated Cosmology Library. The Open Journal of Astrophysics , keywords =. doi:10.21105/astro.2302.05163 , archivePrefix =. 2302.05163 , primaryClass =

View on Pith Pith review arXiv
[193]

Core-collapse supernovae in the Dark Energy Survey: luminosity functions and host galaxy demographics. , keywords =. doi:10.1093/mnras/stad056 , archivePrefix =. 2207.08520 , primaryClass =

View on Pith Pith review arXiv
[194]

Bayesian estimation applied to multiple species. , keywords =. doi:10.1103/PhysRevD.75.103508 , archivePrefix =. astro-ph/0611004 , primaryClass =

View on Pith Pith review arXiv
[195]

Darvishi, Roxana and Stenning, David C. and Hippel, Ted von and Ward, Owen G. , title = ". ArXiv e-prints , year = 2026, month = jan, eid =. doi:10.48550/arXiv.2603.06944 , archivePrefix =. 2603.06944 , archivePrefix =

View on Pith doi:10.48550/arxiv.2603.06944 2026
[196]

The dark energy survey supernova program: investigating beyond- CDM. , keywords =. doi:10.1093/mnras/stae1988 , archivePrefix =. 2406.05048 , primaryClass =

View on Pith Pith review arXiv
[197]

Tests for model misspecification in simulation-based inference: From local distortions to global model checks. , keywords =. doi:10.1103/PhysRevD.111.083013 , archivePrefix =. 2412.15100 , primaryClass =

View on Pith Pith review arXiv
[198]

Peculiar velocities in redshift space: formalism, N-body simulations and perturbation theory. , keywords =. doi:10.1088/1475-7516/2014/05/003 , archivePrefix =. 1312.4214 , primaryClass =

View on Pith Pith review arXiv 2014
[199]

Hawai`i Supernova Flows: Bulk Flow Measurements using SNe Ia in the Optical and NIR. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2606.17142 , archivePrefix =. 2606.17142 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2606.17142
[200]

FlowSN: neural simulation-based inference under realistic selection effects applied to supernova cosmology. , keywords =. doi:10.1093/mnras/stag1046 , archivePrefix =. 2603.11165 , primaryClass =

View on Pith Pith review arXiv
[201]

The colour variability of low-z SNe Ia is entirely explained by dust. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2606.06593 , archivePrefix =. 2606.06593 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2606.06593
[202]

On the origin of the environmental dependence of SN Ia magnitudes: a BayeSN view of the ZTF SN Ia DR2. , keywords =. doi:10.1093/mnras/stag1785 , archivePrefix =. 2605.06799 , adsurl =

View on Pith Pith review arXiv
[203]

Examining extinction distributions for type Ia supernovae in simulated 3D galaxies. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2605.23512 , archivePrefix =. 2605.23512 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2605.23512
[204]

BayeSN and SALT: a comparison of dust inference across SN Ia light-curve models with DES5YR. , keywords =. doi:10.1093/mnras/staf1345 , archivePrefix =. 2410.13747 , primaryClass =

View on Pith Pith review arXiv
[205]

BayeSN Dovekie: Joint Photometric Cross-calibration and SED Modelling of Type Ia Supernovae. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2606.19429 , archivePrefix =. 2606.19429 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2606.19429
[206]

BayeSN-TD: Time Delay and H _ 0 Estimation for Lensed SN H0pe. , keywords =. doi:10.1093/mnras/stag340 , archivePrefix =. 2510.11719 , primaryClass =

View on Pith Pith review arXiv
[207]

Two-population model of type Ia supernovae and their associations with host galaxies in ZTF DR2. arXiv e-prints , keywords =. doi:10.48550/arXiv.2606.17802 , archivePrefix =. 2606.17802 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2606.17802
[208]

SCONE: Supernova Classification with a Convolutional Neural Network. , keywords =. doi:10.3847/1538-3881/ac0824 , archivePrefix =. 2106.04370 , primaryClass =

View on Pith Pith review arXiv
[209]

SuperNNova: an open-source framework for Bayesian, neural network-based supernova classification. , keywords =. doi:10.1093/mnras/stz3312 , archivePrefix =. 1901.06384 , primaryClass =

View on Pith Pith review arXiv 1901
[210]

DASH: Deep Learning for the Automated Spectral Classification of Supernovae and Their Hosts. , keywords =. doi:10.3847/1538-4357/ab48f4 , archivePrefix =. 1903.02557 , primaryClass =

View on Pith Pith review arXiv 1903
[211]

RAPID: Early Classification of Explosive Transients Using Deep Learning. , keywords =. doi:10.1088/1538-3873/ab1609 , archivePrefix =. 1904.00014 , primaryClass =

View on Pith Pith review arXiv 1904
[212]

Avocado: Photometric Classification of Astronomical Transients with Gaussian Process Augmentation. , keywords =. doi:10.3847/1538-3881/ab5182 , archivePrefix =. 1907.04690 , primaryClass =

View on Pith Pith review arXiv 1907
[213]

The Velocity Field Olympics: assessing velocity field reconstructions with direct distance tracers. , keywords =. doi:10.1093/mnras/staf1960 , archivePrefix =. 2502.00121 , primaryClass =

View on Pith arXiv
[214]

Cosmological parameters from the comparison of peculiar velocities with predictions from the 2M++ density field. , keywords =. doi:10.1093/mnras/stv547 , archivePrefix =. 1504.04627 , primaryClass =

View on Pith Pith review arXiv
[215]

The Dark Energy Survey supernova programme: modelling selection efficiency and observed core-collapse supernova contamination. , keywords =. doi:10.1093/mnras/stab1353 , archivePrefix =. 2012.07180 , primaryClass =

View on Pith Pith review arXiv 2012
[216]

polychord: nested sampling for cosmology. , keywords =. doi:10.1093/mnrasl/slv047 , archivePrefix =. 1502.01856 , primaryClass =

View on Pith Pith review arXiv
[217]

UltraNest - a robust, general purpose Bayesian inference engine. J.\ Open Source Software , keywords =. doi:10.21105/joss.03001 , archivePrefix =. 2101.09604 , primaryClass =

View on Pith Pith review arXiv
[218]

Theory of Probability , author=. 1961 , edition=

View on Pith 1961
[219]

The Weighted Likelihood Ratio, Linear Hypotheses on Normal Location Parameters , author=. Ann.\ Math.\ Statistics , year=. doi:10.1214/aoms/1177693507 , url=

View on Pith doi:10.1214/aoms/1177693507
[220]

Evaluating cosmological biases using photometric redshifts for Type Ia Supernova cosmology with the Dark Energy Survey Supernova Program. , keywords =. doi:10.1093/mnras/stae2703 , archivePrefix =. 2407.16744 , primaryClass =

View on Pith Pith review arXiv
[221]

The Dark Energy Survey supernova program: a reanalysis of cosmology results and evidence for evolving dark energy with an updated Type Ia supernova calibration. , keywords =. doi:10.1093/mnras/stag632 , archivePrefix =. 2511.07517 , primaryClass =

View on Pith Pith review arXiv
[222]

skysurvey: a pure python package to simulate the transient sky. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2605.25840 , archivePrefix =. 2605.25840 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2605.25840
[223]

LightCurveLynx: Forward Modeling of Time-Domain Surveys with Application to ZTF SN Ia DR2. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2604.07134 , archivePrefix =. 2604.07134 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2604.07134
[224]

Hybrid Summary Statistics. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2410.07548 , archivePrefix =. 2410.07548 , primaryClass =

View on Pith doi:10.48550/arxiv.2410.07548
[225]

A reassessment of the Pantheon+ and DES 5YR calibration uncertainties: Dovekie. , keywords =. doi:10.1051/0004-6361/202555963 , archivePrefix =. 2506.05471 , primaryClass =

View on Pith Pith review arXiv
[226]

Small-Scale Cosmological Perturbations: an Analytic Approach. , keywords =. doi:10.1086/177989 , archivePrefix =. astro-ph/9510117 , primaryClass =

View on Pith Pith review arXiv
[227]

Cosmological implications of baryon acoustic oscillation measurements. , keywords =. doi:10.1103/PhysRevD.92.123516 , archivePrefix =. 1411.1074 , primaryClass =

View on Pith Pith review arXiv
[228]

The Impact of Observing Strategy on Cosmological Constraints with LSST. , keywords =. doi:10.3847/1538-4365/ac5033 , archivePrefix =. 2104.05676 , primaryClass =

View on Pith Pith review arXiv
[229]

Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Wide-Fast-Deep Survey. ArXiv e-prints , keywords =. doi:10.48550/arXiv.1812.00515 , archivePrefix =. 1812.00515 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.1812.00515
[230]

Type Ia supernova progenitors: a contemporary view of a long-standing puzzle. , keywords =. doi:10.1007/s00159-024-00158-9 , archivePrefix =. 2412.01766 , primaryClass =

View on Pith Pith review arXiv
[231]

The effect of environment on Type Ia supernovae in the Dark Energy Survey three-year cosmological sample. , keywords =. doi:10.1093/mnras/staa3924 , archivePrefix =. 2008.12101 , primaryClass =

View on Pith Pith review arXiv 2008
[232]

Concerning colour: The effect of environment on type Ia supernova colour in the dark energy survey. , keywords =. doi:10.1093/mnras/stac3711 , archivePrefix =. 2208.01357 , primaryClass =

View on Pith Pith review arXiv
[233]

Gaussian mixture models for blended photometric redshifts. , keywords =. doi:10.1093/mnras/stz2687 , archivePrefix =. 1907.10572 , primaryClass =

View on Pith Pith review arXiv 1907
[234]

pop-cosmos: Scaleable Inference of Galaxy Properties and Redshifts with a Data-driven Population Model. , keywords =. doi:10.3847/1538-4357/ad7736 , archivePrefix =. 2406.19437 , primaryClass =

View on Pith Pith review arXiv
[235]

TPZ: photometric redshift PDFs and ancillary information by using prediction trees and random forests. , keywords =. doi:10.1093/mnras/stt574 , archivePrefix =. 1303.7269 , primaryClass =

View on Pith Pith review arXiv
[236]

Nested sampling for physical scientists. Nature Reviews Methods Primers , keywords =. doi:10.1038/s43586-022-00121-x , archivePrefix =. 2205.15570 , primaryClass =

View on Pith Pith review arXiv
[237]

Comparison of dynamical dark energy with CDM in light of DESI DR2. , keywords =. doi:10.1093/mnras/staf2207 , archivePrefix =. 2503.17342 , primaryClass =

View on Pith Pith review arXiv
[238]

A Simulation Based Inference Approach to Modelling of Type Ia Supernova Populations. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2607.28725 , archivePrefix =. 2607.28725 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2607.28725
[239]

jax-SNANA: A GPU-accelerated Supernova Framework for the SBI Era. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2610.19000 , url =

View on Pith Pith review arXiv doi:10.48550/arxiv.2610.19000
[240]

Modular Bayesian Inference for Partially Misspecified Mixtures with Uncertain Class Labels. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2610.27085 , url =

View on Pith Pith review arXiv doi:10.48550/arxiv.2610.27085

Discussion

Disagree with the review, or know something it missed? Leave a comment, highlight any passage above to comment on it, or challenge this review formally.

[1] [1]

Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows , author =. Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics , pages =. 2019 , editor =

View on Pith 2019

[2] [2]

The Pantheon+ analysis: Improving the redshifts and peculiar velocities of Type Ia supernovae used in cosmological analyses. , keywords =. doi:10.1017/pasa.2022.41 , archivePrefix =. 2112.01471 , primaryClass =

View on Pith Pith review arXiv 2022

[3] [3]

James Bradbury and Roy Frostig and Peter Hawkins and Matthew James Johnson and Chris Leary and Dougal Maclaurin and George Necula and Adam Paszke and Jake Vander

View on Pith

[4] [4]

Density estimation by dual ascent of the log-likelihood , author=. Comm. Math. Sci. , volume=. 2010 , publisher=

View on Pith 2010

[5] [5]

Papamakarios, George and Pavlakou, Theo and Murray, Iain , booktitle =. Masked Autoregressive Flow for Density Estimation , url =. 2017 , archivePrefix =

View on Pith 2017

[6] [6]

MADE: Masked Autoencoder for Distribution Estimation , author =. Proceedings of the 32nd International Conference on Machine Learning , pages =. 2015 , editor =

View on Pith 2015

[7] [7]

SIDE-real: Supernova Ia Dust Extinction with truncated marginal neural ratio estimation applied to real data. , keywords =. doi:10.1093/mnras/stae995 , archivePrefix =. 2403.07871 , primaryClass =

View on Pith Pith review arXiv

[8] [8]

The Pantheon+ Analysis: The Full Data Set and Light-curve Release. , keywords =. doi:10.3847/1538-4357/ac8b7a , archivePrefix =. 2112.03863 , primaryClass =

View on Pith Pith review arXiv

[9] [9]

Union through UNITY: Cosmology with 2000 SNe Using a Unified Bayesian Framework. , keywords =. doi:10.3847/1538-4357/adc0a5 , archivePrefix =. 2311.12098 , primaryClass =

View on Pith Pith review arXiv 2000

[10] [11]

Hybrid Monte Carlo , journal =. 1987 , issn =. doi:10.1016/0370-2693(87)91197-X , author =

View on Pith doi:10.1016/0370-2693(87)91197-x 1987

[11] [12]

SimSIMS: Simulation-based Supernova Ia Model Selection with thousands of latent variables. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2311.15650 , archivePrefix =. 2311.15650 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2311.15650

[12] [13]

A family of nonparametric density estimation algorithms , author=. Comm. Pure Applied Math. , volume=. 2013 , publisher=

View on Pith 2013

[13] [14]

The Maximum Mass of Ideal White Dwarfs. , year = 1931, month = jul, volume =. doi:10.1086/143324 , adsurl =

View on Pith doi:10.1086/143324 1931

[14] [15]

A two-parameter luminosity correction for Type IA supernovae. , keywords =

View on Pith

[15] [16]

The Absolute Magnitudes of Type IA Supernovae. , keywords =. doi:10.1086/186970 , adsurl =

View on Pith doi:10.1086/186970

[16] [17]

Hubble Residuals of Nearby Type Ia Supernovae are Correlated with Host Galaxy Masses. , keywords =. doi:10.1088/0004-637X/715/2/743 , archivePrefix =. 0912.0929 , primaryClass =

View on Pith Pith review arXiv

[17] [18]

The dependence of Type Ia Supernovae luminosities on their host galaxies. , keywords =. doi:10.1111/j.1365-2966.2010.16731.x , archivePrefix =. 1003.5119 , primaryClass =

View on Pith Pith review arXiv 2010

[18] [19]

The Effect of Host Galaxies on Type Ia Supernovae in the SDSS-II Supernova Survey. , keywords =. doi:10.1088/0004-637X/722/1/566 , archivePrefix =. 1005.4687 , primaryClass =

View on Pith Pith review arXiv

[19] [20]

Host Galaxy Properties and Hubble Residuals of Type Ia Supernovae from the Nearby Supernova Factory. , keywords =. doi:10.1088/0004-637X/770/2/108 , archivePrefix =. 1304.4720 , primaryClass =

View on Pith Pith review arXiv

[20] [21]

Improved cosmological constraints from a joint analysis of the SDSS-II and SNLS supernova samples. , keywords =. doi:10.1051/0004-6361/201423413 , archivePrefix =. 1401.4064 , primaryClass =

View on Pith Pith review arXiv

[21] [22]

SALT2: using distant supernovae to improve the use of type Ia supernovae as distance indicators. , keywords =. doi:10.1051/0004-6361:20066930 , archivePrefix =. astro-ph/0701828 , primaryClass =

View on Pith Pith review arXiv

[22] [23]

The Supernova Legacy Survey 3-year sample: Type Ia supernovae photometric distances and cosmological constraints. , keywords =. doi:10.1051/0004-6361/201014468 , archivePrefix =. 1010.4743 , primaryClass =

View on Pith Pith review arXiv

[23] [24]

First cosmology results using Type Ia supernova from the Dark Energy Survey: simulations to correct supernova distance biases. , keywords =. doi:10.1093/mnras/stz463 , archivePrefix =. 1811.02379 , primaryClass =

View on Pith Pith review arXiv

[24] [25]

simsurvey: estimating transient discovery rates for the Zwicky transient facility. , keywords =. doi:10.1088/1475-7516/2019/10/005 , archivePrefix =. 1902.03923 , primaryClass =

View on Pith Pith review arXiv 2019

[25] [26]

SNANA: A Public Software Package for Supernova Analysis. , keywords =. doi:10.1086/605984 , archivePrefix =. 0908.4280 , primaryClass =

View on Pith Pith review arXiv

[26] [27]

Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant. , keywords =. doi:10.1086/300499 , archivePrefix =. astro-ph/9805201 , primaryClass =

View on Pith Pith review arXiv

[27] [28]

Hubble Tension: The Evidence of New Physics. Universe , keywords =. doi:10.3390/universe9020094 , archivePrefix =. 2302.05709 , primaryClass =

View on Pith Pith review arXiv

[28] [29]

Discovery of a supernova explosion at half the age of the Universe. , keywords =. doi:10.1038/34124 , archivePrefix =. astro-ph/9712212 , primaryClass =

View on Pith Pith review arXiv

[29] [30]

First Cosmology Results using Type Ia Supernovae from the Dark Energy Survey: Constraints on Cosmological Parameters. , keywords =. doi:10.3847/2041-8213/ab04fa , archivePrefix =. 1811.02374 , primaryClass =

View on Pith Pith review arXiv

[30] [31]

Future Type Ia Supernova Data as Tests of Dark Energy from Modified Friedmann Equations. , keywords =. doi:10.1086/376899 , archivePrefix =. astro-ph/0302064 , primaryClass =

View on Pith Pith review arXiv

[31] [32]

Cosmic Distances Calibrated to 1\. , keywords =. doi:10.3847/2041-8213/abdbaf , archivePrefix =. 2012.08534 , primaryClass =

View on Pith Pith review arXiv 2012

[32] [33]

Planck 2018 results. VI. Cosmological parameters. , keywords =. doi:10.1051/0004-6361/201833910 , archivePrefix =. 1807.06209 , primaryClass =

View on Pith Pith review arXiv 2018

[33] [34]

It's Dust: Solving the Mysteries of the Intrinsic Scatter and Host-galaxy Dependence of Standardized Type Ia Supernova Brightnesses. , keywords =. doi:10.3847/1538-4357/abd69b , archivePrefix =. 2004.10206 , primaryClass =

View on Pith Pith review arXiv 2004

[34] [35]

Sensitivity of the Hubble Constant Determination to Cepheid Calibration. , keywords =. doi:10.3847/1538-4357/ac756e , archivePrefix =. 2105.11461 , primaryClass =

View on Pith Pith review arXiv

[35] [36]

The Hubble Tension Revisited: Additional Local Distance Ladder Uncertainties. , keywords =. doi:10.3847/1538-4357/ac7c19 , archivePrefix =. 2106.09400 , primaryClass =

View on Pith Pith review arXiv

[36] [37]

A BayeSN distance ladder: H _ 0 from a consistent modelling of type ia supernovae from the optical to the near infrared. , keywords =. doi:10.1093/mnras/stad1590 , archivePrefix =. 2211.07657 , primaryClass =

View on Pith Pith review arXiv

[37] [38]

Measurements of the Hubble Constant: Tensions in Perspective. , keywords =. doi:10.3847/1538-4357/ac0e95 , archivePrefix =. 2106.15656 , primaryClass =

View on Pith Pith review arXiv

[38] [39]

A Uniform Type Ia Supernova Distance Ladder with the Zwicky Transient Facility: Absolute Calibration Based on the Tip of the Red Giant Branch Method. , keywords =. doi:10.3847/1538-4357/ac7ceb , archivePrefix =. 2203.04241 , primaryClass =

View on Pith Pith review arXiv

[39] [40]

The Pantheon+ Analysis: Cosmological Constraints. , keywords =. doi:10.3847/1538-4357/ac8e04 , archivePrefix =. 2202.04077 , primaryClass =

View on Pith Pith review arXiv

[40] [41]

The Type Ia Supernova Color-Magnitude Relation and Host Galaxy Dust: A Simple Hierarchical Bayesian Model. , keywords =. doi:10.3847/1538-4357/aa6038 , archivePrefix =. 1609.04470 , primaryClass =

View on Pith Pith review arXiv

[41] [42]

Variational inference for acceleration of SN Ia photometric distance estimation with BayeSN. , keywords =. doi:10.1093/mnras/stae2465 , archivePrefix =. 2405.06013 , primaryClass =

View on Pith Pith review arXiv

[42] [43]

Supernova Limits on the Cosmic Equation of State. , keywords =. doi:10.1086/306495 , archivePrefix =. astro-ph/9806396 , primaryClass =

View on Pith Pith review arXiv

[43] [44]

The Supernova Legacy Survey: measurement of _ M , _ and w from the first year data set. , keywords =. doi:10.1051/0004-6361:20054185 , archivePrefix =. astro-ph/0510447 , primaryClass =

View on Pith Pith review arXiv

[44] [45]

Observational Constraints on the Nature of Dark Energy: First Cosmological Results from the ESSENCE Supernova Survey. , keywords =. doi:10.1086/518642 , archivePrefix =. astro-ph/0701041 , primaryClass =

View on Pith Pith review arXiv

[45] [46]

The Carnegie Supernova Project: First Near-Infrared Hubble Diagram to z -0.5ex 0.7. , keywords =. doi:10.1088/0004-637X/704/2/1036 , archivePrefix =. 0907.4524 , primaryClass =

View on Pith Pith review arXiv

[46] [47]

Improved Cosmological Constraints from New, Old, and Combined Supernova Data Sets. , keywords =. doi:10.1086/589937 , archivePrefix =. 0804.4142 , primaryClass =

View on Pith Pith review arXiv

[47] [48]

Improved constraints on cosmological parameters from Type Ia supernova data. , keywords =. doi:10.1111/j.1365-2966.2011.19584.x , archivePrefix =. 1102.3237 , primaryClass =

View on Pith Pith review arXiv 2011

[48] [49]

UNITY: Confronting Supernova Cosmology's Statistical and Systematic Uncertainties in a Unified Bayesian Framework. , keywords =. doi:10.1088/0004-637X/813/2/137 , archivePrefix =. 1507.01602 , primaryClass =

View on Pith Pith review arXiv

[49] [50]

BAHAMAS: New Analysis of Type Ia Supernovae Reveals Inconsistencies with Standard Cosmology. , keywords =. doi:10.3847/0004-637X/827/1/1 , archivePrefix =. 1510.05954 , primaryClass =

View on Pith Pith review arXiv

[50] [51]

Type Ia Supernova Light-Curve Inference: Hierarchical Bayesian Analysis in the Near-Infrared. , keywords =. doi:10.1088/0004-637X/704/1/629 , archivePrefix =. 0908.0536 , primaryClass =

View on Pith Pith review arXiv

[51] [52]

A hierarchical Bayesian SED model for Type Ia supernovae in the optical to near-infrared. , keywords =. doi:10.1093/mnras/stab3496 , archivePrefix =. 2008.07538 , primaryClass =

View on Pith Pith review arXiv 2008

[52] [53]

Testing the consistency of dust laws in SN Ia host galaxies: a BAYESN examination of Foundation DR1. , keywords =. doi:10.1093/mnras/stab2849 , archivePrefix =. 2102.05678 , primaryClass =

View on Pith Pith review arXiv

[53] [54]

Type Ia Supernova Light Curve Inference: Hierarchical Models in the Optical and Near-infrared. , keywords =. doi:10.1088/0004-637X/731/2/120 , archivePrefix =. 1011.5910 , primaryClass =

View on Pith Pith review arXiv

[54] [55]

The Carnegie Supernova Project: Analysis of the First Sample of Low-Redshift Type-Ia Supernovae. , keywords =. doi:10.1088/0004-6256/139/1/120 , archivePrefix =. 0910.3317 , primaryClass =

View on Pith Pith review arXiv

[55] [56]

Measuring Ejecta Velocity Improves Type Ia Supernova Distances. , keywords =. doi:10.1088/0004-637X/729/1/55 , archivePrefix =. 1011.4517 , primaryClass =

View on Pith Pith review arXiv

[56] [57]

Phillips, M. M. , year=. Near-Infrared Properties of Type Ia Supernovae , volume=. Publications of the Astronomical Society of Australia , publisher=. doi:10.1071/AS11056 , number=

View on Pith doi:10.1071/as11056

[57] [58]

Constraining the SN Ia host galaxy dust law distribution and mass step: hierarchical BAYESN analysis of optical and near-infrared light curves. , keywords =. doi:10.1093/mnras/stac2714 , archivePrefix =. 2209.10552 , primaryClass =

View on Pith Pith review arXiv

[58] [59]

Near-infrared Supernova Ia Distances: Host Galaxy Extinction and Mass-step Corrections Revisited. , keywords =. doi:10.3847/1538-4357/ac2f9e , archivePrefix =. 2105.06236 , primaryClass =

View on Pith Pith review arXiv

[59] [60]

Using rest-frame optical and NIR data from the RAISIN survey to explore the redshift evolution of dust laws in SN Ia host galaxies. , keywords =. doi:10.1093/mnras/stae1111 , archivePrefix =. 2402.18624 , primaryClass =

View on Pith Pith review arXiv

[60] [61]

The Carnegie Supernova Project: Light-curve Fitting with SNooPy. , keywords =. doi:10.1088/0004-6256/141/1/19 , archivePrefix =. 1010.4040 , primaryClass =

View on Pith Pith review arXiv

[61] [62]

The Carnegie Supernova Project: Intrinsic Colors of Type Ia Supernovae. , keywords =. doi:10.1088/0004-637X/789/1/32 , archivePrefix =. 1405.3934 , primaryClass =

View on Pith Pith review arXiv

[62] [63]

The Carnegie Supernova Project: Absolute Calibration and the Hubble Constant. , keywords =. doi:10.3847/1538-4357/aae51c , archivePrefix =. 1809.06381 , primaryClass =

View on Pith Pith review arXiv

[63] [64]

The Carnegie Supernova Project. I. Third Photometry Data Release of Low-redshift Type Ia Supernovae and Other White Dwarf Explosions. , keywords =. doi:10.3847/1538-3881/aa8df0 , archivePrefix =. 1709.05146 , primaryClass =

View on Pith Pith review arXiv

[64] [65]

LSST: From Science Drivers to Reference Design and Anticipated Data Products. , keywords =. doi:10.3847/1538-4357/ab042c , archivePrefix =. 0805.2366 , primaryClass =

View on Pith Pith review arXiv

[65] [66]

Simulations of the WFIRST Supernova Survey and Forecasts of Cosmological Constraints. , keywords =. doi:10.3847/1538-4357/aac08b , archivePrefix =. 1702.01747 , primaryClass =

View on Pith Pith review arXiv

[66] [67]

Carnegie Supernova Project-II: Extending the Near-infrared Hubble Diagram for Type Ia Supernovae to z 0.1. , keywords =. doi:10.1088/1538-3873/aae8bd , archivePrefix =. 1810.09252 , primaryClass =

View on Pith Pith review arXiv

[67] [68]

The Young Supernova Experiment: Survey Goals, Overview, and Operations. , keywords =. doi:10.3847/1538-4357/abd7f5 , archivePrefix =. 2010.09724 , primaryClass =

View on Pith Pith review arXiv 2010

[68] [69]

The Zwicky Transient Facility Type Ia supernova survey: first data release and results. , keywords =. doi:10.1093/mnras/stab3093 , archivePrefix =. 2110.07256 , primaryClass =

View on Pith Pith review arXiv

[69] [70]

Carnegie Supernova Project-II: The Near-infrared Spectroscopy Program. , keywords =. doi:10.1088/1538-3873/aae961 , archivePrefix =. 1810.08213 , primaryClass =

View on Pith Pith review arXiv

[70] [71]

Spectroscopy of Type Ia Supernovae by the Carnegie Supernova Project. , keywords =. doi:10.1088/0004-637X/773/1/53 , archivePrefix =. 1305.6997 , primaryClass =

View on Pith Pith review arXiv

[71] [72]

The Spectroscopic Diversity of Type Ia Supernovae. , keywords =. doi:10.1088/0004-6256/143/5/126 , archivePrefix =. 1203.4832 , primaryClass =

View on Pith Pith review arXiv

[72] [73]

Abundance stratification in Type Ia supernovae - IV. The luminous, peculiar SN 1991T. , keywords =. doi:10.1093/mnras/stu1777 , archivePrefix =. 1409.0116 , primaryClass =

View on Pith Pith review arXiv

[73] [74]

Photometric and Spectroscopic Properties of Type Ia Supernova 2018oh with Early Excess Emission from the Kepler 2 Observations. , keywords =. doi:10.3847/1538-4357/aaec74 , archivePrefix =. 1811.10056 , primaryClass =

View on Pith Pith review arXiv

[74] [75]

Multi-Object Spectroscopy with Optical Fibres. Very Large Telescopes and their Instrumentation, Vol. 2 , year = 1988, series =

View on Pith 1988

[75] [76]

APERO: A PipelinE to Reduce Observations-Demonstration with SPIRou. , keywords =. doi:10.1088/1538-3873/ac9e74 , archivePrefix =. 2211.01358 , primaryClass =

View on Pith Pith review arXiv

[76] [77]

On the Compared Accuracy and Reliability of Spectroscopic and Photometric Redshift Measurements. , keywords =. doi:10.1086/321777 , archivePrefix =. astro-ph/0007447 , primaryClass =

View on Pith Pith review arXiv

[77] [78]

K-Corrections and Spectral Templates of Type Ia Supernovae. , keywords =. doi:10.1086/518232 , archivePrefix =. astro-ph/0703529 , primaryClass =

View on Pith Pith review arXiv

[78] [79]

Carnegie Supernova Project. II. Near-infrared Spectral Diversity and Template of Type Ia Supernovae. , keywords =. doi:10.3847/1538-4357/acc100 , archivePrefix =. 2211.05998 , primaryClass =

View on Pith Pith review arXiv

[79] [80]

Spectroscopic diversity of Type Ia supernovae , author =

View on Pith

[80] [81]

Rasmussen, Carl Edward and Williams, Christopher K. I. , title = ". 2005 , month =. doi:10.7551/mitpress/3206.001.0001 , url =

View on Pith doi:10.7551/mitpress/3206.001.0001 2005

[81] [82]

Spectrophotometric templates for core-collapse supernovae and their application in simulations of time-domain surveys. , keywords =. doi:10.1093/mnras/stz2448 , archivePrefix =. 1908.05228 , primaryClass =

View on Pith Pith review arXiv 1908

[82] [83]

What can Gaussian processes really tell us about supernova light curves? Consequences for Type II(b) morphologies and genealogies. , keywords =. doi:10.1093/mnras/stac3523 , archivePrefix =. 2206.14816 , primaryClass =

View on Pith Pith review arXiv

[83] [84]

Investigating the diversity of Type Ia supernova spectra with the open-source relational data base KAEPORA. , keywords =. doi:10.1093/mnras/stz1209 , archivePrefix =. 1905.02204 , primaryClass =

View on Pith Pith review arXiv 1905

[84] [85]

A possible distance bias for type Ia supernovae with different ejecta velocities. , keywords =. doi:10.1093/mnras/staa577 , archivePrefix =. 2002.09490 , primaryClass =

View on Pith Pith review arXiv 2002

[85] [86]

Berkeley Supernova Ia Program - I. Observations, data reduction and spectroscopic sample of 582 low-redshift Type Ia supernovae. , keywords =. doi:10.1111/j.1365-2966.2012.21270.x , archivePrefix =. 1202.2128 , primaryClass =

View on Pith Pith review arXiv 2012

[86] [87]

Properties of Type Ia Supernova , author =

View on Pith

[87] [88]

Velocity Evolution and the Intrinsic Color of Type Ia Supernovae. , keywords =. doi:10.1088/0004-637X/742/2/89 , archivePrefix =. 1107.3555 , primaryClass =

View on Pith Pith review arXiv

[88] [89]

Optical and infrared observations of SN 2002dj: some possible common properties of fast-expanding Type Ia supernovae. , keywords =. doi:10.1111/j.1365-2966.2008.13434.x , archivePrefix =. 0805.1089 , primaryClass =

View on Pith Pith review arXiv 2008

[89] [90]

Direct Analysis of Spectra of the Peculiar Type Ia Supernova 2000cx. , keywords =. doi:10.1086/382950 , archivePrefix =. astro-ph/0401324 , primaryClass =

View on Pith Pith review arXiv

[90] [91]

Near-infrared light curves of Type Ia supernovae: studying properties of the second maximum. , keywords =. doi:10.1093/mnras/stu2716 , archivePrefix =. 1502.00568 , primaryClass =

View on Pith Pith review arXiv

[91] [92]

Subpercent Photometry: Faint DA White Dwarf Spectrophotometric Standards for Astrophysical Observatories. , keywords =. doi:10.3847/1538-4365/ab0557 , archivePrefix =. 1811.12534 , primaryClass =

View on Pith Pith review arXiv

[92] [93]

Systematic Uncertainties Associated with the Cosmological Analysis of the First Pan-STARRS1 Type Ia Supernova Sample. , keywords =. doi:10.1088/0004-637X/795/1/45 , archivePrefix =. 1310.3824 , primaryClass =

View on Pith Pith review arXiv

[93] [94]

Techniques and Review of Absolute Flux Calibration from the Ultraviolet to the Mid-Infrared. , keywords =. doi:10.1086/677655 , archivePrefix =. 1406.1707 , primaryClass =

View on Pith Pith review arXiv

[94] [95]

Hubble Space Telescope CALSPEC Flux Standards: Sirius (and Vega). , keywords =. doi:10.1088/0004-6256/147/6/127 , adsurl =

View on Pith doi:10.1088/0004-6256/147/6/127

[95] [96]

The No-U-Turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo. , author=. J. Mach. Learn. Res. , volume=

View on Pith

[96] [97]

Probabilistic programming in Python using PyMC3 , author=. PeerJ Computer Science , volume=. 2016 , publisher=

View on Pith 2016

[97] [98]

Non-LTE Line-blanketed Model Atmospheres of Hot Stars. I. Hybrid Complete Linearization/Accelerated Lambda Iteration Method. , keywords =. doi:10.1086/175226 , adsurl =

View on Pith doi:10.1086/175226

[98] [99]

All-Sky Faint DA White Dwarf Spectrophotometric Standards for Astrophysical Observatories: The Complete Sample. arXiv e-prints , keywords =. doi:10.48550/arXiv.2305.07563 , archivePrefix =. 2305.07563 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2305.07563

[99] [100]

Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro. ArXiv e-prints , keywords =. doi:10.48550/arXiv.1912.11554 , archivePrefix =. 1912.11554 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.1912.11554 1912

[100] [101]

Measuring the Hubble constant with Type Ia supernovae as near-infrared standard candles. , keywords =. doi:10.1051/0004-6361/201731501 , archivePrefix =. 1707.00715 , primaryClass =

View on Pith Pith review arXiv

[101] [102]

Binaries and Supernovae of Type I. , year = 1973, month = dec, volume =. doi:10.1086/152565 , adsurl =

View on Pith doi:10.1086/152565 1973

[102] [103]

The evolution of low-mass close binaries influenced by the radiation of gravitational waves and by a magnetic stellar wind. , keywords =. doi:10.1086/162455 , adsurl =

View on Pith doi:10.1086/162455

[103] [104]

Paolo A. Mazzali and Friedrich K. Röpke and Stefano Benetti and Wolfgang Hillebrandt , title =. Science , volume =. 2007 , doi =. https://www.science.org/doi/pdf/10.1126/science.1136259 , abstract =

View on Pith doi:10.1126/science.1136259 2007

[104] [105]

POLYCHORD: next-generation nested sampling. , keywords =. doi:10.1093/mnras/stv1911 , archivePrefix =. 1506.00171 , primaryClass =

View on Pith Pith review arXiv

[105] [106]

Evidence Networks: simple losses for fast, amortized, neural Bayesian model comparison. Machine Learning: Sci.\ Technol. , keywords =. doi:10.1088/2632-2153/ad1a4d , archivePrefix =. 2305.11241 , primaryClass =

View on Pith Pith review arXiv

[106] [107]

Clarifying the Hubble constant tension with a Bayesian hierarchical model of the local distance ladder. , keywords =. doi:10.1093/mnras/sty418 , archivePrefix =. 1707.00007 , primaryClass =

View on Pith Pith review arXiv

[107] [108]

The Dust Attenuation Law in Galaxies. , keywords =. doi:10.1146/annurev-astro-032620-021933 , archivePrefix =. 2001.03181 , primaryClass =

View on Pith Pith review arXiv 2001

[108] [109]

Draine, B.T. , title =. Annual Review of Astronomy and Astrophysics , volume =. 2003 , doi =. https://doi.org/10.1146/annurev.astro.41.011802.094840 , abstract =

View on Pith Pith review doi:10.1146/annurev.astro.41.011802.094840 2003

[109] [110]

An Analysis of the Shapes of Interstellar Extinction Curves. V. The IR-through-UV Curve Morphology. , keywords =. doi:10.1086/518158 , archivePrefix =. 0705.0154 , primaryClass =

View on Pith Pith review arXiv

[110] [111]

An Analysis of the Shapes of Interstellar Extinction Curves. VI. The Near-IR Extinction Law. , keywords =. doi:10.1088/0004-637X/699/2/1209 , archivePrefix =. 0905.0133 , primaryClass =

View on Pith Pith review arXiv

[111] [112]

The effects of varying colour-luminosity relations on Type Ia supernova science. , keywords =. doi:10.1093/mnras/stab2802 , archivePrefix =. 2009.13230 , primaryClass =

View on Pith Pith review arXiv 2009

[112] [113]

Relative Intrinsic Scatter in Hierarchical Type Ia Supernova Sibling Analyses: Application to SNe 2021hpr, 1997bq, and 2008fv in NGC 3147. , keywords =. doi:10.3847/1538-4357/acf7bb , archivePrefix =. 2209.10558 , primaryClass =

View on Pith Pith review arXiv

[113] [114]

On some relations in stellar statistics. Medd.\ Lunds Astron.\ Obser.\ Serie I , year = 1922, month = mar, volume =

View on Pith 1922

[114] [115]

Correcting Type Ia Supernova Distances for Selection Biases and Contamination in Photometrically Identified Samples. , keywords =. doi:10.3847/1538-4357/836/1/56 , archivePrefix =. 1610.04677 , primaryClass =

View on Pith Pith review arXiv

[115] [116]

A Bayesian approach to truncated data sets: An application to Malmquist bias in Supernova Cosmology. ArXiv e-prints , keywords =. doi:10.48550/arXiv.1804.02474 , archivePrefix =. 1804.02474 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.1804.02474

[116] [117]

Mixture density networks , author=. 1994 , number =

View on Pith 1994

[117] [118]

Variational Inference with Normalizing Flows , author =. Proceedings of the 32nd International Conference on Machine Learning , pages =. 2015 , editor =

View on Pith 2015

[118] [119]

Hermans, Joeri and Begy, Volodimir and Louppe, Gilles , booktitle =. Likelihood-free. 2020 , editor =

View on Pith 2020

[119] [120]

SICRET: Supernova Ia Cosmology with truncated marginal neural Ratio EsTimation. , keywords =. doi:10.1093/mnras/stac3785 , archivePrefix =. 2209.06733 , primaryClass =

View on Pith Pith review arXiv

[120] [121]

Amortized bayesian inference for supernovae in the era of the vera rubin observatory using normalizing flows , author=. arXiv preprint arXiv:2211.04480 , year=

View on Pith Pith review arXiv

[121] [122]

Measurements of and from 42 High-Redshift Supernovae. , keywords =. doi:10.1086/307221 , adsurl =

View on Pith Pith review doi:10.1086/307221

[122] [123]

SN 2022ann: a Type Icn supernova from a dwarf galaxy that reveals helium in its circumstellar environment. , keywords =. doi:10.1093/mnras/stad1433 , archivePrefix =. 2211.05134 , primaryClass =

View on Pith arXiv

[123] [124]

Fast likelihood-free cosmology with neural density estimators and active learning. , keywords =. doi:10.1093/mnras/stz1960 , archivePrefix =. 1903.00007 , primaryClass =

View on Pith Pith review arXiv 1903

[124] [125]

George Papamakarios and Eric Nalisnick and Danilo Jimenez Rezende and Shakir Mohamed and Balaji Lakshminarayanan , title =. J.\ Machine Learning Res. , year =

View on Pith

[125] [126]

Eli Bingham and Jonathan P. Chen and Martin Jankowiak and Fritz Obermeyer and Neeraj Pradhan and Theofanis Karaletsos and Rohit Singh and Paul A. Szerlip and Paul Horsfall and Noah D. Goodman , title =. J. Machine Learning Res. , volume =. 2019 , url =

View on Pith 2019

[126] [127]

The Effect of Peculiar Velocities on Supernova Cosmology. , keywords =. doi:10.1088/0004-637X/741/1/67 , archivePrefix =. 1012.2912 , primaryClass =

View on Pith Pith review arXiv

[127] [128]

Redshift evolution of the underlying type Ia supernova stretch distribution. , keywords =. doi:10.1051/0004-6361/202038447 , archivePrefix =. 2005.09441 , primaryClass =

View on Pith Pith review arXiv 2005

[128] [129]

ZTF SN Ia DR2: The diversity and relative rates of the thermonuclear supernova population. , keywords =. doi:10.1051/0004-6361/202451852 , archivePrefix =. 2406.01434 , primaryClass =

View on Pith arXiv

[129] [130]

ZTF SN Ia DR2: Environmental dependencies of stretch and luminosity for a volume-limited sample of 1000 type Ia supernovae. , keywords =. doi:10.1051/0004-6361/202450378 , archivePrefix =. 2405.20965 , primaryClass =

View on Pith Pith review arXiv

[130] [131]

ZTF SN Ia DR2: Colour standardisation of type Ia supernovae and its dependence on the environment. , keywords =. doi:10.1051/0004-6361/202450943 , archivePrefix =. 2406.02072 , primaryClass =

View on Pith Pith review arXiv

[131] [132]

The Pantheon+ Analysis: Forward Modeling the Dust and Intrinsic Color Distributions of Type Ia Supernovae, and Quantifying Their Impact on Cosmological Inferences. , keywords =. doi:10.3847/1538-4357/aca273 , archivePrefix =. 2112.04456 , primaryClass =

View on Pith Pith review arXiv

[132] [133]

Scalable hierarchical BayeSN inference: investigating dependence of SN Ia host galaxy dust properties on stellar mass and redshift. , keywords =. doi:10.1093/mnras/stae1202 , archivePrefix =. 2401.08755 , primaryClass =

View on Pith Pith review arXiv

[133] [134]

SALT3: An Improved Type Ia Supernova Model for Measuring Cosmic Distances. , keywords =. doi:10.3847/1538-4357/ac30d8 , archivePrefix =. 2104.07795 , primaryClass =

View on Pith Pith review arXiv

[134] [135]

Accounting for Selection Effects in Supernova Cosmology with Simulation-Based Inference and Hierarchical Bayesian Modelling. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2407.15923 , archivePrefix =. 2407.15923 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2407.15923

[135] [136]

STAR NRE: solving supernova selection effects with set-based truncated auto-regressive neural ratio estimation. , keywords =. doi:10.1088/1475-7516/2025/07/031 , archivePrefix =. 2409.03837 , primaryClass =

View on Pith Pith review arXiv 2025

[136] [137]

Andrew Gelman and Donald B. Rubin , title =. Statistical Sci. , number =. 1992 , doi =

View on Pith 1992

[137] [138]

Rank-normalization, folding, and localization: An improved R-hat for assessing convergence of MCMC (with Discussion). Bayesian Analysis , keywords =. doi:10.1214/20-BA1221 , archivePrefix =. 1903.08008 , primaryClass =

View on Pith Pith review arXiv 1903

[138] [139]

Optimizing The Integrator Step Size for Hamiltonian Monte Carlo. ArXiv e-prints , keywords =. doi:10.48550/arXiv.1411.6669 , archivePrefix =. 1411.6669 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.1411.6669

[139] [140]

A Conceptual Introduction to Hamiltonian Monte Carlo. ArXiv e-prints , keywords =. doi:10.48550/arXiv.1701.02434 , archivePrefix =. 1701.02434 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.1701.02434

[140] [141]

Matthew D. Hoffman and Andrew Gelman , title =. Journal of Machine Learning Research , year =

View on Pith

[141] [142]

Reassessing the ZTF Volume-limited Type Ia Supernova Sample and Its Implications for Continuous, Dust-dependent Models of Intrinsic Scatter. , keywords =. doi:10.3847/1538-4357/ae122d , archivePrefix =. 2505.04686 , primaryClass =

View on Pith Pith review arXiv

[142] [143]

Binning is Sinning: Redemption for Hubble Diagram Using Photometrically Classified Type Ia Supernovae. , keywords =. doi:10.3847/2041-8213/ace34d , archivePrefix =. 2306.05819 , primaryClass =

View on Pith Pith review arXiv

[143] [144]

Binning is Sinning (Supernova Version): The Impact of Self-calibration in Cosmological Analyses with Type Ia Supernovae. , keywords =. doi:10.3847/2041-8213/abf4db , archivePrefix =. 2012.05900 , primaryClass =

View on Pith Pith review arXiv 2012

[144] [145]

CIGaRS I: combined simulation-based inference from type Ia supernovae and host photometry. Nature Astronomy , keywords =. doi:10.1038/s41550-026-02842-5 , archivePrefix =. 2508.15899 , primaryClass =

View on Pith Pith review arXiv

[145] [146]

Hierarchical Simulation-Based Inference of Supernova Power Sources and their Physical Properties. arXiv e-prints , keywords =. doi:10.48550/arXiv.2510.14202 , archivePrefix =. 2510.14202 , primaryClass =

View on Pith doi:10.48550/arxiv.2510.14202

[146] [147]

Hierarchical Neural Simulation-Based Inference Over Event Ensembles , author=. Transactions on Machine Learning Research , issn=. 2024 , url=

View on Pith 2024

[147] [148]

Improved Distances to Type Ia Supernovae with Multicolor Light-Curve Shapes: MLCS2k2. , keywords =. doi:10.1086/512054 , archivePrefix =. astro-ph/0612666 , primaryClass =

View on Pith Pith review arXiv

[148] [149]

Distance measures in cosmology. ArXiv e-prints , keywords =. doi:10.48550/arXiv.astro-ph/9905116 , archivePrefix =. astro-ph/9905116 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.astro-ph/9905116

[149] [150]

A Measurement of the Rate of Type Ia Supernovae at Redshift z 0.1 from the First Season of the SDSS-II Supernova Survey. , keywords =. doi:10.1086/587733 , archivePrefix =. 0801.3297 , primaryClass =

View on Pith Pith review arXiv

[150] [151]

DAmodel: hierarchical Bayesian modelling of DA white dwarfs for spectrophotometric calibration. , keywords =. doi:10.1093/mnras/staf629 , archivePrefix =. 2412.08809 , primaryClass =

View on Pith Pith review arXiv

[151] [152]

Type Ia Supernova Colors and Ejecta Velocities: Hierarchical Bayesian Regression with Non-Gaussian Distributions. , keywords =. doi:10.1088/0004-637X/797/2/75 , archivePrefix =. 1402.7079 , primaryClass =

View on Pith Pith review arXiv

[152] [153]

The subtle statistics of the distance ladder: On the distance prior and selection effects. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2511.03394 , archivePrefix =. 2511.03394 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2511.03394

[153] [154]

4MOST: Project overview and information for the First Call for Proposals. The Messenger , keywords =. doi:10.18727/0722-6691/5117 , archivePrefix =. 1903.02464 , primaryClass =

View on Pith Pith review arXiv 1903

[154] [155]

TiDES: The 4MOST Time Domain Extragalactic Survey. , keywords =. doi:10.3847/1538-4357/adff4e , archivePrefix =. 2501.16311 , primaryClass =

View on Pith Pith review arXiv

[155] [156]

Using Host Galaxy Photometric Redshifts to Improve Cosmological Constraints with Type Ia Supernovae in the LSST Era. , keywords =. doi:10.3847/1538-4357/acb057 , archivePrefix =. 2210.07560 , primaryClass =

View on Pith Pith review arXiv

[156] [157]

Models and Simulations for the Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC). , keywords =. doi:10.1088/1538-3873/ab26f1 , archivePrefix =. 1903.11756 , primaryClass =

View on Pith Pith review arXiv 1903

[157] [158]

Measuring Type Ia Supernova Populations of Stretch and Color and Predicting Distance Biases. , keywords =. doi:10.3847/2041-8205/822/2/L35 , archivePrefix =. 1603.01559 , primaryClass =

View on Pith Pith review arXiv

[158] [159]

Correcting for the Effects of Interstellar Extinction. , keywords =. doi:10.1086/316293 , archivePrefix =. astro-ph/9809387 , primaryClass =

View on Pith Pith review arXiv

[159] [160]

Measuring Reddening with Sloan Digital Sky Survey Stellar Spectra and Recalibrating SFD. , keywords =. doi:10.1088/0004-637X/737/2/103 , archivePrefix =. 1012.4804 , primaryClass =

View on Pith Pith review arXiv

[160] [161]

Five-Year Wilkinson Microwave Anisotropy Probe Observations: Cosmological Interpretation. , keywords =. doi:10.1088/0067-0049/180/2/330 , archivePrefix =. 0803.0547 , primaryClass =

View on Pith Pith review arXiv

[161] [162]

A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2110.06581 , archivePrefix =. 2110.06581 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2110.06581

[162] [163]

The Dark Energy Survey: Cosmology Results with 1500 New High-redshift Type Ia Supernovae Using the Full 5 yr Data Set. , keywords =. doi:10.3847/2041-8213/ad6f9f , archivePrefix =. 2401.02929 , primaryClass =

View on Pith Pith review arXiv

[163] [164]

Evolving dark energy or supernovae systematics?. , keywords =. doi:10.1093/mnras/staf301 , archivePrefix =. 2408.07175 , primaryClass =

View on Pith Pith review arXiv

[164] [165]

The axis of systematic bias in SN Ia cosmology and implications for DESI 2024 results. , keywords =. doi:10.1093/mnras/staf779 , archivePrefix =. 2409.18668 , primaryClass =

View on Pith Pith review arXiv 2024

[165] [166]

Strong progenitor age bias in supernova cosmology ─ II. Alignment with DESI BAO and signs of a non-accelerating universe. , keywords =. doi:10.1093/mnras/staf1685 , archivePrefix =. 2510.13121 , primaryClass =

View on Pith arXiv

[166] [167]

Still Accelerating: Type Ia supernova cosmology is robust to host galaxy age evolution. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2601.13785 , archivePrefix =. 2601.13785 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2601.13785

[167] [168]

SNIa Cosmology Analysis Results from Simulated LSST Images: From Difference Imaging to Constraints on Dark Energy. , keywords =. doi:10.3847/1538-4357/ac7a37 , archivePrefix =. 2111.06858 , primaryClass =

View on Pith Pith review arXiv

[168] [169]

ZTF SN Ia DR2: Improved SN Ia colors through expanded dimensionality with SALT3+. , keywords =. doi:10.1051/0004-6361/202452578 , archivePrefix =. 2502.09713 , primaryClass =

View on Pith Pith review arXiv

[169] [170]

A revised SALT2 surface for fitting Type Ia supernova light curves. , keywords =. doi:10.1093/mnras/stab962 , archivePrefix =. 2104.00172 , primaryClass =

View on Pith Pith review arXiv

[170] [171]

ZTF SN Ia DR2: Evidence of changing dust distribution with redshift using type Ia supernovae. , keywords =. doi:10.1051/0004-6361/202450391 , archivePrefix =. 2406.06215 , primaryClass =

View on Pith Pith review arXiv

[171] [172]

Space Distribution and Luminosity Functions of Quasi-Stellar Radio Sources. , year = 1968, month = feb, volume =. doi:10.1086/149446 , adsurl =

View on Pith doi:10.1086/149446 1968

[172] [173]

Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog. , keywords =. doi:10.3847/2041-8213/abe949 , archivePrefix =. 2010.14533 , primaryClass =

View on Pith Pith review arXiv 2010

[173] [174]

Stellar masses and star formation histories for 10 ^ 5 galaxies from the Sloan Digital Sky Survey. , keywords =. doi:10.1046/j.1365-8711.2003.06291.x , archivePrefix =. astro-ph/0204055 , primaryClass =

View on Pith Pith review arXiv 2003

[174] [175]

Occurrence Rates of Planets Orbiting FGK Stars: Combining Kepler DR25, Gaia DR2, and Bayesian Inference. , keywords =. doi:10.3847/1538-3881/ab31ab , archivePrefix =. 1902.01417 , primaryClass =

View on Pith Pith review arXiv 1902

[175] [176]

Prevalence of Earth-size planets orbiting Sun-like stars. Proc.\ Natl.\ Acad.\ Sci. , keywords =. doi:10.1073/pnas.1319909110 , archivePrefix =. 1311.6806 , primaryClass =

View on Pith Pith review arXiv

[176] [177]

The ejected mass distribution of Type Ia supernovae: a significant rate of non-Chandrasekhar-mass progenitors. , keywords =. doi:10.1093/mnras/stu1808 , archivePrefix =. 1408.6601 , primaryClass =

View on Pith Pith review arXiv

[177] [178]

Lightcurve Modelling of 2,205 ZTF DR2 Type -0.5ex Supernovae: Implications for SN Ia Physics and Cosmology. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2602.02677 , archivePrefix =. 2602.02677 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2602.02677

[178] [179]

Banana Split: Improved Cosmological Constraints with Two Light-Curve-Shape and Color Populations Using Union3.1+UNITY1.8. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2601.19854 , archivePrefix =. 2601.19854 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2601.19854

[179] [180]

Union3.1: Self-consistent Measurements of Host Galaxy Properties for 2000 Type Ia Supernovae. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2601.19424 , archivePrefix =. 2601.19424 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2601.19424 2000

[180] [181]

The frontier of simulation-based inference. Proc.\ Natl.\ Acad.\ Sci. , keywords =. doi:10.1073/pnas.1912789117 , archivePrefix =. 1911.01429 , primaryClass =

View on Pith Pith review arXiv 1911

[181] [182]

Data-driven dust inference at mid-to-high Galactic latitudes using probabilistic machine learning. , keywords =. doi:10.1093/mnras/staf2147 , archivePrefix =. 2508.05781 , primaryClass =

View on Pith arXiv

[182] [183]

Misspecification-robust amortised simulation-based inference using variational methods. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2509.05724 , archivePrefix =. 2509.05724 , primaryClass =

View on Pith doi:10.48550/arxiv.2509.05724

[183] [184]

DESI 2024 VI: cosmological constraints from the measurements of baryon acoustic oscillations. , keywords =. doi:10.1088/1475-7516/2025/02/021 , archivePrefix =. 2404.03002 , primaryClass =

View on Pith Pith review arXiv 2024

[184] [185]

Comparing the DES-SN5YR and Pantheon+ SN cosmology analyses: investigation based on 'evolving dark energy or supernovae systematics'?. , keywords =. doi:10.1093/mnras/staf943 , archivePrefix =. 2501.06664 , primaryClass =

View on Pith Pith review arXiv

[185] [186]

Selection Functions in Astronomical Data Modeling, with the Space Density of White Dwarfs as a Worked Example. , keywords =. doi:10.3847/1538-3881/ac0c13 , archivePrefix =. 2106.07653 , primaryClass =

View on Pith Pith review arXiv

[186] [187]

Improved weak lensing photometric redshift calibration via StratLearn and hierarchical modelling. , keywords =. doi:10.1093/mnras/stae2243 , archivePrefix =. 2401.04687 , primaryClass =

View on Pith Pith review arXiv

[187] [188]

A Fully Photometric Approach to Type Ia Supernova Cosmology in the LSST Era: Host-galaxy Redshifts and Supernova Classification. , keywords =. doi:10.3847/1538-4357/ae7a41 , archivePrefix =. 2512.06319 , primaryClass =

View on Pith Pith review arXiv

[188] [189]

Environmental Dependence of Type Ia Supernovae in Low-redshift Galaxy Clusters. , keywords =. doi:10.3847/1538-4357/ad0e0f , archivePrefix =. 2306.01088 , primaryClass =

View on Pith Pith review arXiv

[189] [190]

FlowJAX: Distributions and Normalizing Flows in Jax , author =. 2024 , doi =

View on Pith 2024

[190] [191]

Colm Talbot and Amanda Farah and Shanika Galaudage and Jacob Golomb and Hui Tong , title =. Journal of Open Source Software , doi =. 2025 , publisher =

View on Pith 2025

[191] [192]

JAX-COSMO: An End-to-End Differentiable and GPU Accelerated Cosmology Library. The Open Journal of Astrophysics , keywords =. doi:10.21105/astro.2302.05163 , archivePrefix =. 2302.05163 , primaryClass =

View on Pith Pith review arXiv

[192] [193]

Core-collapse supernovae in the Dark Energy Survey: luminosity functions and host galaxy demographics. , keywords =. doi:10.1093/mnras/stad056 , archivePrefix =. 2207.08520 , primaryClass =

View on Pith Pith review arXiv

[193] [194]

Bayesian estimation applied to multiple species. , keywords =. doi:10.1103/PhysRevD.75.103508 , archivePrefix =. astro-ph/0611004 , primaryClass =

View on Pith Pith review arXiv

[194] [195]

Darvishi, Roxana and Stenning, David C. and Hippel, Ted von and Ward, Owen G. , title = ". ArXiv e-prints , year = 2026, month = jan, eid =. doi:10.48550/arXiv.2603.06944 , archivePrefix =. 2603.06944 , archivePrefix =

View on Pith doi:10.48550/arxiv.2603.06944 2026

[195] [196]

The dark energy survey supernova program: investigating beyond- CDM. , keywords =. doi:10.1093/mnras/stae1988 , archivePrefix =. 2406.05048 , primaryClass =

View on Pith Pith review arXiv

[196] [197]

Tests for model misspecification in simulation-based inference: From local distortions to global model checks. , keywords =. doi:10.1103/PhysRevD.111.083013 , archivePrefix =. 2412.15100 , primaryClass =

View on Pith Pith review arXiv

[197] [198]

Peculiar velocities in redshift space: formalism, N-body simulations and perturbation theory. , keywords =. doi:10.1088/1475-7516/2014/05/003 , archivePrefix =. 1312.4214 , primaryClass =

View on Pith Pith review arXiv 2014

[198] [199]

Hawai`i Supernova Flows: Bulk Flow Measurements using SNe Ia in the Optical and NIR. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2606.17142 , archivePrefix =. 2606.17142 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2606.17142

[199] [200]

FlowSN: neural simulation-based inference under realistic selection effects applied to supernova cosmology. , keywords =. doi:10.1093/mnras/stag1046 , archivePrefix =. 2603.11165 , primaryClass =

View on Pith Pith review arXiv

[200] [201]

The colour variability of low-z SNe Ia is entirely explained by dust. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2606.06593 , archivePrefix =. 2606.06593 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2606.06593

[201] [202]

On the origin of the environmental dependence of SN Ia magnitudes: a BayeSN view of the ZTF SN Ia DR2. , keywords =. doi:10.1093/mnras/stag1785 , archivePrefix =. 2605.06799 , adsurl =

View on Pith Pith review arXiv

[202] [203]

Examining extinction distributions for type Ia supernovae in simulated 3D galaxies. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2605.23512 , archivePrefix =. 2605.23512 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2605.23512

[203] [204]

BayeSN and SALT: a comparison of dust inference across SN Ia light-curve models with DES5YR. , keywords =. doi:10.1093/mnras/staf1345 , archivePrefix =. 2410.13747 , primaryClass =

View on Pith Pith review arXiv

[204] [205]

BayeSN Dovekie: Joint Photometric Cross-calibration and SED Modelling of Type Ia Supernovae. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2606.19429 , archivePrefix =. 2606.19429 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2606.19429

[205] [206]

BayeSN-TD: Time Delay and H _ 0 Estimation for Lensed SN H0pe. , keywords =. doi:10.1093/mnras/stag340 , archivePrefix =. 2510.11719 , primaryClass =

View on Pith Pith review arXiv

[206] [207]

Two-population model of type Ia supernovae and their associations with host galaxies in ZTF DR2. arXiv e-prints , keywords =. doi:10.48550/arXiv.2606.17802 , archivePrefix =. 2606.17802 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2606.17802

[207] [208]

SCONE: Supernova Classification with a Convolutional Neural Network. , keywords =. doi:10.3847/1538-3881/ac0824 , archivePrefix =. 2106.04370 , primaryClass =

View on Pith Pith review arXiv

[208] [209]

SuperNNova: an open-source framework for Bayesian, neural network-based supernova classification. , keywords =. doi:10.1093/mnras/stz3312 , archivePrefix =. 1901.06384 , primaryClass =

View on Pith Pith review arXiv 1901

[209] [210]

DASH: Deep Learning for the Automated Spectral Classification of Supernovae and Their Hosts. , keywords =. doi:10.3847/1538-4357/ab48f4 , archivePrefix =. 1903.02557 , primaryClass =

View on Pith Pith review arXiv 1903

[210] [211]

RAPID: Early Classification of Explosive Transients Using Deep Learning. , keywords =. doi:10.1088/1538-3873/ab1609 , archivePrefix =. 1904.00014 , primaryClass =

View on Pith Pith review arXiv 1904

[211] [212]

Avocado: Photometric Classification of Astronomical Transients with Gaussian Process Augmentation. , keywords =. doi:10.3847/1538-3881/ab5182 , archivePrefix =. 1907.04690 , primaryClass =

View on Pith Pith review arXiv 1907

[212] [213]

The Velocity Field Olympics: assessing velocity field reconstructions with direct distance tracers. , keywords =. doi:10.1093/mnras/staf1960 , archivePrefix =. 2502.00121 , primaryClass =

View on Pith arXiv

[213] [214]

Cosmological parameters from the comparison of peculiar velocities with predictions from the 2M++ density field. , keywords =. doi:10.1093/mnras/stv547 , archivePrefix =. 1504.04627 , primaryClass =

View on Pith Pith review arXiv

[214] [215]

The Dark Energy Survey supernova programme: modelling selection efficiency and observed core-collapse supernova contamination. , keywords =. doi:10.1093/mnras/stab1353 , archivePrefix =. 2012.07180 , primaryClass =

View on Pith Pith review arXiv 2012

[215] [216]

polychord: nested sampling for cosmology. , keywords =. doi:10.1093/mnrasl/slv047 , archivePrefix =. 1502.01856 , primaryClass =

View on Pith Pith review arXiv

[216] [217]

UltraNest - a robust, general purpose Bayesian inference engine. J.\ Open Source Software , keywords =. doi:10.21105/joss.03001 , archivePrefix =. 2101.09604 , primaryClass =

View on Pith Pith review arXiv

[217] [218]

Theory of Probability , author=. 1961 , edition=

View on Pith 1961

[218] [219]

The Weighted Likelihood Ratio, Linear Hypotheses on Normal Location Parameters , author=. Ann.\ Math.\ Statistics , year=. doi:10.1214/aoms/1177693507 , url=

View on Pith doi:10.1214/aoms/1177693507

[219] [220]

Evaluating cosmological biases using photometric redshifts for Type Ia Supernova cosmology with the Dark Energy Survey Supernova Program. , keywords =. doi:10.1093/mnras/stae2703 , archivePrefix =. 2407.16744 , primaryClass =

View on Pith Pith review arXiv

[220] [221]

The Dark Energy Survey supernova program: a reanalysis of cosmology results and evidence for evolving dark energy with an updated Type Ia supernova calibration. , keywords =. doi:10.1093/mnras/stag632 , archivePrefix =. 2511.07517 , primaryClass =

View on Pith Pith review arXiv

[221] [222]

skysurvey: a pure python package to simulate the transient sky. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2605.25840 , archivePrefix =. 2605.25840 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2605.25840

[222] [223]

LightCurveLynx: Forward Modeling of Time-Domain Surveys with Application to ZTF SN Ia DR2. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2604.07134 , archivePrefix =. 2604.07134 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2604.07134

[223] [224]

Hybrid Summary Statistics. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2410.07548 , archivePrefix =. 2410.07548 , primaryClass =

View on Pith doi:10.48550/arxiv.2410.07548

[224] [225]

A reassessment of the Pantheon+ and DES 5YR calibration uncertainties: Dovekie. , keywords =. doi:10.1051/0004-6361/202555963 , archivePrefix =. 2506.05471 , primaryClass =

View on Pith Pith review arXiv

[225] [226]

Small-Scale Cosmological Perturbations: an Analytic Approach. , keywords =. doi:10.1086/177989 , archivePrefix =. astro-ph/9510117 , primaryClass =

View on Pith Pith review arXiv

[226] [227]

Cosmological implications of baryon acoustic oscillation measurements. , keywords =. doi:10.1103/PhysRevD.92.123516 , archivePrefix =. 1411.1074 , primaryClass =

View on Pith Pith review arXiv

[227] [228]

The Impact of Observing Strategy on Cosmological Constraints with LSST. , keywords =. doi:10.3847/1538-4365/ac5033 , archivePrefix =. 2104.05676 , primaryClass =

View on Pith Pith review arXiv

[228] [229]

Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Wide-Fast-Deep Survey. ArXiv e-prints , keywords =. doi:10.48550/arXiv.1812.00515 , archivePrefix =. 1812.00515 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.1812.00515

[229] [230]

Type Ia supernova progenitors: a contemporary view of a long-standing puzzle. , keywords =. doi:10.1007/s00159-024-00158-9 , archivePrefix =. 2412.01766 , primaryClass =

View on Pith Pith review arXiv

[230] [231]

The effect of environment on Type Ia supernovae in the Dark Energy Survey three-year cosmological sample. , keywords =. doi:10.1093/mnras/staa3924 , archivePrefix =. 2008.12101 , primaryClass =

View on Pith Pith review arXiv 2008

[231] [232]

Concerning colour: The effect of environment on type Ia supernova colour in the dark energy survey. , keywords =. doi:10.1093/mnras/stac3711 , archivePrefix =. 2208.01357 , primaryClass =

View on Pith Pith review arXiv

[232] [233]

Gaussian mixture models for blended photometric redshifts. , keywords =. doi:10.1093/mnras/stz2687 , archivePrefix =. 1907.10572 , primaryClass =

View on Pith Pith review arXiv 1907

[233] [234]

pop-cosmos: Scaleable Inference of Galaxy Properties and Redshifts with a Data-driven Population Model. , keywords =. doi:10.3847/1538-4357/ad7736 , archivePrefix =. 2406.19437 , primaryClass =

View on Pith Pith review arXiv

[234] [235]

TPZ: photometric redshift PDFs and ancillary information by using prediction trees and random forests. , keywords =. doi:10.1093/mnras/stt574 , archivePrefix =. 1303.7269 , primaryClass =

View on Pith Pith review arXiv

[235] [236]

Nested sampling for physical scientists. Nature Reviews Methods Primers , keywords =. doi:10.1038/s43586-022-00121-x , archivePrefix =. 2205.15570 , primaryClass =

View on Pith Pith review arXiv

[236] [237]

Comparison of dynamical dark energy with CDM in light of DESI DR2. , keywords =. doi:10.1093/mnras/staf2207 , archivePrefix =. 2503.17342 , primaryClass =

View on Pith Pith review arXiv

[237] [238]

A Simulation Based Inference Approach to Modelling of Type Ia Supernova Populations. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2607.28725 , archivePrefix =. 2607.28725 , primaryClass =

View on Pith Pith review arXiv doi:10.48550/arxiv.2607.28725

[238] [239]

jax-SNANA: A GPU-accelerated Supernova Framework for the SBI Era. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2610.19000 , url =

View on Pith Pith review arXiv doi:10.48550/arxiv.2610.19000

[239] [240]

Modular Bayesian Inference for Partially Misspecified Mixtures with Uncertain Class Labels. ArXiv e-prints , keywords =. doi:10.48550/arXiv.2610.27085 , url =

View on Pith Pith review arXiv doi:10.48550/arxiv.2610.27085