Rotational transits of WASP-121 b observed with JWST/NIRSpec and NIRISS show asymmetric light curves and phase-dependent molecular absorption revealing stronger evening than morning terminator temperature gradients.
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Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro
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abstract
NumPyro is a lightweight library that provides an alternate NumPy backend to the Pyro probabilistic programming language with the same modeling interface, language primitives and effect handling abstractions. Effect handlers allow Pyro's modeling API to be extended to NumPyro despite its being built atop a fundamentally different JAX-based functional backend. In this work, we demonstrate the power of composing Pyro's effect handlers with the program transformations that enable hardware acceleration, automatic differentiation, and vectorization in JAX. In particular, NumPyro provides an iterative formulation of the No-U-Turn Sampler (NUTS) that can be end-to-end JIT compiled, yielding an implementation that is much faster than existing alternatives in both the small and large dataset regimes.
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representative citing papers
NumPyro delivers a JIT-compilable iterative NUTS sampler by composing Pyro effect handlers with JAX transformations, achieving faster performance than prior implementations.
Splitting an attack across more coordinating agents lowers per-commit monitor suspicion, making distributed attacks harder to detect than single-agent attacks.
A standardizing coordinate transform turns PTA Fourier coefficients into near-standard normals so HMC/NUTS on GPU recovers NANOGrav-scale posteriors in ~15 minutes.
Hierarchical Bayesian power-law fits to early ZTF light curves of 972 SNe Ia yield population parameters for rise time, index, and color evolution, revealing a bifurcation with SALT2 stretch.
A hierarchical Bayesian approach with multivariate Gaussian population prior reduces bias in demographic inference of SN Ia power-law rise parameters compared to individual fitting.
Bayesian workflow diagnostics outperform unit tests for detecting and repairing statistically misspecified LLM-generated probabilistic programs across benchmarks and real generation tasks.
A new RTU grid method models the lensing source as a Gaussian process on a ray-transformed uniform grid, achieving comparable fits with roughly half the pixels per dimension and higher ELBOs on mock data.
A hierarchical Bayesian framework that uses the empirical anti-correlation between AGN variability amplitude and luminosity to infer cosmological parameters from moderate-baseline light curves via importance reweighting.
All 18 audited MLLMs exhibit order sensitivity with per-facet flip rates of 24-50%, exceeding same-order decoder noise.
Multidimensional IRT analysis of 34k FCI administrations identifies 22 robust misconception dimensions and computes student/class scores revealing varied post-instruction remediation patterns.
DREAM enables exact-gradient Bayesian calibration of nuclear models via offline SVD emulation of parameter-dependent operators, demonstrated by rapid HMC convergence on an 18-parameter CDCC analysis of d+58Ni scattering.
Equivalent Wishart Ansatz for kernel renormalization in Bayesian MLPs and CNNs in the proportional regime, with tests showing good agreement on benchmarks.
acopula enables polynomial-time exact inference for arbitrary nested Archimedean copulas with censoring via Taylor-mode AD on user-defined generators.
A new queryable binary dataset combining cross-build diversity, temporal history, and CVE labels with linked metadata for vulnerability research.
Derives Wasserstein bounds and explicit hyperparameter tuning rules for annealed Langevin dynamics in compositional score-based SBI, proving Linhart et al. (2026) allows larger steps and fewer total steps than Geffner et al. (2023) in the Gaussian case.
Bayesian nonparametric model for dynamic sparse networks with overlapping communities via completely random measures and latent Markov processes.
Large longitudinal RCT finds high rates of following AI personal advice but no sustained well-being gains versus a hobbies control condition.
AMIGO is an end-to-end differentiable forward model of JWST AMI that corrects detector systematics to recover high-precision astrometry and detect close high-contrast companions.
Symbolic regression yields an emulator for the radial Fourier transform of the Sérsic profile that enables 2.5 times faster galaxy profile fitting with minimal accuracy loss.
Introduces HICOBIAN, a differentiable fuzzy hierarchical cosmic-web bias model using sigmoid gradients for smooth region transitions, enabling accurate Bayesian field-level reconstruction of primordial density fields validated by Fourier-space statistics.
Extends NPE to mixed discrete-continuous parameter spaces via a factorized inference network combining an autoregressive classifier and generative model, trained jointly to yield accurate calibrated posteriors.
Variational predictive resampling iteratively imputes data from a variational predictive to produce posterior samples that converge to the exact Bayesian posterior in Gaussian models where mean-field VI retains a gap.
A fully Bayesian pixel-based Doppler imaging framework uses Gaussian Process priors and Hamiltonian Monte Carlo to simultaneously infer surface maps and geometric parameters from spectral data.
citing papers explorer
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Atmospheric asymmetries in WASP-121 b revealed by rotational transits detected with JWST
Rotational transits of WASP-121 b observed with JWST/NIRSpec and NIRISS show asymmetric light curves and phase-dependent molecular absorption revealing stronger evening than morning terminator temperature gradients.
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Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro
NumPyro delivers a JIT-compilable iterative NUTS sampler by composing Pyro effect handlers with JAX transformations, achieving faster performance than prior implementations.
-
Multi-Agent AI Control: Distributed Attacks Hamper Per-Instance Monitors
Splitting an attack across more coordinating agents lowers per-commit monitor suspicion, making distributed attacks harder to detect than single-agent attacks.
-
A new framework for lightning-fast gravitational wave analysis of pulsar timing data
A standardizing coordinate transform turns PTA Fourier coefficients into near-standard normals so HMC/NUTS on GPU recovers NANOGrav-scale posteriors in ~15 minutes.
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Decoding the Early-Time Light Curves of Type Ia Supernovae. II. Population Parameters of One Thousand ZTF Supernovae
Hierarchical Bayesian power-law fits to early ZTF light curves of 972 SNe Ia yield population parameters for rise time, index, and color evolution, revealing a bifurcation with SALT2 stretch.
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Decoding the Early-Time Light Curves of Type Ia Supernovae. I. A Hierarchical Bayesian Framework for Demographic Inference
A hierarchical Bayesian approach with multivariate Gaussian population prior reduces bias in demographic inference of SN Ia power-law rise parameters compared to individual fitting.
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Calibration, Not Compilation: Detecting and Repairing Misspecified Probabilistic Programs Written by Language Models
Bayesian workflow diagnostics outperform unit tests for detecting and repairing statistically misspecified LLM-generated probabilistic programs across benchmarks and real generation tasks.
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Gaussian processes on ray-guided transformed uniform grids for fast, flexible, and auto-differentiable adaptive source reconstruction in lens modelling
A new RTU grid method models the lensing source as a Gaussian process on a ray-transformed uniform grid, achieving comparable fits with roughly half the pixels per dimension and higher ELBOs on mock data.
-
A hierarchical Bayesian framework for cosmology using Type 1 AGN variability
A hierarchical Bayesian framework that uses the empirical anti-correlation between AGN variability amplitude and luminosity to infer cosmological parameters from moderate-baseline light curves via importance reweighting.
-
Same Evidence, Different Answer: Auditing Order Sensitivity in Multimodal Large Language Models
All 18 audited MLLMs exhibit order sensitivity with per-facet flip rates of 24-50%, exceeding same-order decoder noise.
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Discovering Misconceptions and Misunderstandings From Administrations of Research-Designed Multiple Choice Instruments
Multidimensional IRT analysis of 34k FCI administrations identifies 22 robust misconception dimensions and computes student/class scores revealing varied post-instruction remediation patterns.
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High-Dimensional Bayesian Calibration of Expensive Nuclear Models with Differentiable Emulation
DREAM enables exact-gradient Bayesian calibration of nuclear models via offline SVD emulation of parameter-dependent operators, demonstrated by rapid HMC convergence on an 18-parameter CDCC analysis of d+58Ni scattering.
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Kernel Renormalization in Bayesian Deep Neural Networks: the Equivalent Wishart Ansatz in the Proportional Regime
Equivalent Wishart Ansatz for kernel renormalization in Bayesian MLPs and CNNs in the proportional regime, with tests showing good agreement on benchmarks.
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Archimedean Copula Inference via Taylor-Mode AD
acopula enables polynomial-time exact inference for arbitrary nested Archimedean copulas with censoring via Taylor-mode AD on user-defined generators.
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ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage
A new queryable binary dataset combining cross-build diversity, temporal history, and CVE labels with linked metadata for vulnerability research.
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Theoretical guidelines for annealed Langevin dynamics in compositional simulation-based inference
Derives Wasserstein bounds and explicit hyperparameter tuning rules for annealed Langevin dynamics in compositional score-based SBI, proving Linhart et al. (2026) allows larger steps and fewer total steps than Geffner et al. (2023) in the Gaussian case.
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Dynamic sparse graphs with overlapping communities
Bayesian nonparametric model for dynamic sparse networks with overlapping communities via completely random measures and latent Markov processes.
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People readily follow personal advice from AI but it does not improve their well-being
Large longitudinal RCT finds high rates of following AI personal advice but no sustained well-being gains versus a hobbies control condition.
-
AMIGO: a Data-Driven Calibration of the JWST Interferometer
AMIGO is an end-to-end differentiable forward model of JWST AMI that corrects detector systematics to recover high-precision astrometry and detect close high-contrast companions.
-
Using Symbolic Regression to Emulate the Radial Fourier Transform of the S\'ersic profile for Fast, Accurate and Differentiable Galaxy Profile Fitting
Symbolic regression yields an emulator for the radial Fourier transform of the Sérsic profile that enables 2.5 times faster galaxy profile fitting with minimal accuracy loss.
-
Differentiable Fuzzy Cosmic-Web for Field Level Inference
Introduces HICOBIAN, a differentiable fuzzy hierarchical cosmic-web bias model using sigmoid gradients for smooth region transitions, enabling accurate Bayesian field-level reconstruction of primordial density fields validated by Fourier-space statistics.
-
Mixed neural posterior estimation for simulators with discrete and continuous parameters
Extends NPE to mixed discrete-continuous parameter spaces via a factorized inference network combining an autoregressive classifier and generative model, trained jointly to yield accurate calibrated posteriors.
-
Variational predictive resampling
Variational predictive resampling iteratively imputes data from a variational predictive to produce posterior samples that converge to the exact Bayesian posterior in Gaussian models where mean-field VI retains a gap.
-
Bayesian Doppler Imaging: Simultaneous Inference of Surface Maps and Geometric Parameters
A fully Bayesian pixel-based Doppler imaging framework uses Gaussian Process priors and Hamiltonian Monte Carlo to simultaneously infer surface maps and geometric parameters from spectral data.
-
ADELIA: Automatic Differentiation for Efficient Laplace Inference Approximations
ADELIA is the first AD-enabled INLA system that computes exact hyperparameter gradients via a structure-exploiting multi-GPU backward pass, delivering 4.2-7.9x per-gradient speedups and 5-8x better energy efficiency than finite differences on models with up to 1.9 million latent variables.
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Archival Multiband Gravitational-Wave Signals from Massive Black Hole Binary Mergers
Massive black hole binary mergers produce orphaned low-frequency signals in PTA pulsar terms that can be stacked for archival multiband gravitational-wave detection.
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Distinct spin properties and astrophysical origin of low mass binary black holes in gravitational wave data
Hierarchical Bayesian analysis of GWTC-5.0 data identifies a mass transition at 15.2 solar masses separating distinct effective-spin distributions, pointing to different formation channels for low-mass binary black holes.
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Kinematic detection of dusty outflows from active galactic nuclei: Polycyclic aromatic hydrocarbon kinematics of type 2 quasars with JWST/MIRI spectroscopy
PAH 11.3 µm velocity maps reveal dusty outflows in three QSO2s at high Eddington ratio, after disk subtraction, matching molecular residuals and prior theoretical expectations.
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HIcosmo: a differentiable JAX-based framework for cosmology inference
HIcosmo is a new JAX-based differentiable framework for background cosmology inference that matches Cobaya results while delivering 8.7x CPU and up to 20x GPU speedups.
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Shape-Constrained Bayesian Active Learning of Self-Limiting Saturation Curves
Bayesian monotonic I-spline regression with uncertainty sampling learns self-limiting saturation curves to within noise using as few as seven measurements across five kinetic families.
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Learning Dynamical Systems from Multiple Sparse Datasets: A Hierarchical Bayesian Modeling Approach
A hierarchical Bayesian framework pools information across sparse dynamical system datasets via a shared population distribution to improve parameter inference and prediction over unpooled approaches.
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A thorough investigation of cross-correlation estimators for stochastic gravitational-wave background searches in ground-based detector data
Reformulation of frequency-domain narrowband cross-correlation estimators for SGWB searches provides new expressions for estimators and covariances, while showing that widely used prior expressions still yield correct posteriors and log-Bayes factors.
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Scalable Bayesian Additive Models for Stellar Flare Detection via Amortized Gaussian Process Inference and Hidden Markov Models
A VAE-based surrogate for Celerite GPs is embedded in an additive GP+HMM model to achieve scalable Bayesian inference for stellar flare detection.
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Calibration of an Analog-to-Digital Conversion Nonlinearity in JWST/NIRISS
A data-driven model for periodic ADC integral nonlinearity in JWST/NIRISS is fitted to ramp residuals and applied to correct the ERS1366 WASP-39b transmission spectrum, reducing systematics at the 30ppm level.
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GenSBI: Generative Methods for Simulation-Based Inference in JAX
GenSBI delivers JAX-native implementations of generative SBI methods with transformer backbones and reports near-ideal calibration scores on standard benchmarks.
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A Strongly Parametrized Mass Ratio Model for the Stable Mass Transfer Channel: a Case Study of the $10 \, \rm{M}_{\odot}$ Peak
A parametrized analytical model for BBH mass ratios from the stable mass transfer channel is derived and applied to the 10 solar-mass peak in GWTC-4, favoring little mass-ratio reversal.
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AI4BayesCode: From Natural Language Descriptions to Validated Modular Stateful Bayesian Samplers
A new LLM-based system generates and validates runnable modular MCMC samplers directly from natural-language Bayesian model descriptions, reporting success on 120 of 132 benchmark models.
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On the Reparameterization Between Cartesian Position-Velocity Vectors and Orbital Elements in the Kepler Problem
Compact analytic Jacobians are derived for reparameterizing Keplerian orbits between orbital elements and Cartesian states, correcting a singularity in the Skowron et al. (2011) microlensing model and improving MCMC efficiency in astrometric fitting.
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Forbidden Formation Histories: The Binary Black Hole Merger Rate Disfavors Long Delay Times
Deconvolution of the GWTC-4.0 BBH merger rate reveals that long-delay tails in the delay time distribution are forbidden, constraining progenitor formation histories to decline more steeply than the star formation rate and disfavoring shallow power-law DTDs such as stable mass transfer.
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Stochastic gravitational-wave background search using data from five pulsar timing arrays
Combined five-PTA dataset yields posterior on SGWB power-law amplitude and index consistent with nonzero signal but below 5-sigma significance, with reconstructed angular correlations matching the Hellings-Downs prediction.
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OzDES Reverberation Mapping of Active Galactic Nuclei: Final Data Release, Black-Hole Mass Results, & Scaling Relations
A final data release of 62 reverberation-mapped AGN black hole masses and recalibrated R–L scaling relations, reporting ~0.25 dex scatter for Hβ/MgII and revised CIV masses.
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Photon counting readout for detection and inference of gravitational waves from neutron star merger remnants
Photon counting readout detects weak postmerger gravitational wave signals at a rate of about 1 in 100 for SNR 0.2 and yields a twofold improvement in neutron star radius measurement after 20,000 events.
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Image reconstruction with the JWST Interferometer
Dorito enables diffraction-limited image reconstruction from JWST AMI observations by deconvolving images or Fourier observables using maximum entropy and total variation regularization.
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RefineStat: Efficient Exploration for Probabilistic Program Synthesis
RefineStat improves small language model performance on probabilistic program synthesis by adding semantic constraint enforcement and diagnostic-aware refinement, producing syntactically and statistically reliable code that often matches larger models.
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Scalable Spatiotemporal Inference with Biased Scan Attention Transformer Neural Processes
BSA-TNP is a new neural process model with KRBlocks and biased scan attention that claims to match top accuracy while scaling inference to over 1M points in under a minute on a single GPU and supporting translation invariance.
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A search for periodic AGN variability in $\textit{Gaia}$ Data Release 3
Systematic search of 377k Gaia DR3 AGN light curves finds no reliable periodic SMBHB candidates after red-noise modeling and empirical false-alarm testing; all survivors lie in the few-cycle regime.
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A "Black Hole Star" Reveals the Remarkable Gas-Enshrouded Hearts of the Little Red Dots
A source 660 million years after the Big Bang is interpreted as a black hole star with a dust-free dense gas atmosphere, implying Little Red Dots have black hole masses overestimated by orders of magnitude.
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Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space
LLMs perform in-context learning as trajectories through a structured low-dimensional conceptual belief space, with the structure visible in both behavior and internal representations and causally manipulable via interventions.
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A hierarchical Bayesian pipeline for soliton-plus-NFW inference on SPARC rotation curves: diagnostics and prior-boundary behaviour
A hierarchical Bayesian pipeline applied to 106 SPARC galaxies yields posteriors that reach prior boundaries for soliton parameters, indicating no detectable interior population-level soliton within the Schive-normalized model and standard priors.
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What You Don't Know Won't Hurt You: Self-Consistent Hierarchical Inference with Unknown Follow-up Selection Strategies
Hierarchical Bayesian inference allows accurate recovery of intrinsic astrophysical source populations even when follow-up selection is unknown and correlated with parameters of interest.