Paper Citation Record · LEDGER

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$

As of 12 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2608.08007.

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Observation 29bf134d-7f89-4ad1-9bee-cc0c81840e5e · outbound

This paper cites Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant

Reference 1

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This paper cites As shown in Fig.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ As shown in Fig

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This paper cites Exploring the expansion history of the uni- verse,.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Exploring the expansion history of the uni- verse,

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This paper cites Measurements of Ω and Λ from 42 High Redshift Super- novae,.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Measurements of Ω and Λ from 42 High Redshift Super- novae,

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This paper cites Accelerating Universes with Scaling Dark Matter.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Accelerating Universes with Scaling Dark Matter

Reference 6

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Observation bf58aa94-152c-4956-9c22-db234f1466e4 · outbound

This paper cites DESI DR2 Results II: Measurements of Baryon Acoustic Oscillations and Cosmological Constraints.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ DESI DR2 Results II: Measurements of Baryon Acoustic Oscillations and Cosmological Constraints

Reference 7

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This paper cites A Comprehensive Measurement of the Local Value of the Hubble Constant with 1 km/s/Mpc Uncertainty from the Hubble Space Telescope and the SH0ES Team.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ A Comprehensive Measurement of the Local Value of the Hubble Constant with 1 km/s/Mpc Uncertainty from the Hubble Space Telescope and the SH0ES Team

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Planck 2018 results. VI. Cosmological parameters

Reference 9

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This paper cites Reconstruc- tion of dark energy and late-time cosmic expansion using the Weighted Function Regression method,.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Reconstruc- tion of dark energy and late-time cosmic expansion using the Weighted Function Regression method,

Reference 10

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This paper cites Reconstruction of dark energy and expansion dynamics using Gaussian processes.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Reconstruction of dark energy and expansion dynamics using Gaussian processes

Reference 11

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This paper cites Reconstructing equation of state of dark energy with principal component analysis.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Reconstructing equation of state of dark energy with principal component analysis

Reference 12

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This paper cites Distance Priors from Planck Final Release.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Distance Priors from Planck Final Release

Reference 13

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This paper cites Reconstructing dark energy with model independent methods after DESI DR2,.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Reconstructing dark energy with model independent methods after DESI DR2,

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This paper cites How the Dark Energy Can Reconcile \textit{Planck} with Local Determination of the Hubble Constant.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ How the Dark Energy Can Reconcile \textit{Planck} with Local Determination of the Hubble Constant

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This paper cites Reconstruction of the Dark Energy equation of state from latest data: the impact of theoretical priors.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Reconstruction of the Dark Energy equation of state from latest data: the impact of theoretical priors

Reference 16

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This paper cites Dynamical dark energy in light of the latest observations.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Dynamical dark energy in light of the latest observations

Reference 17

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Observation 692278b1-8709-4b9e-bf70-c6ac951bb1d8 · outbound

This paper cites Reconstruction of the Dark Energy Equation of State from the Latest Obser- vations,.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Reconstruction of the Dark Energy Equation of State from the Latest Obser- vations,

Reference 18

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This paper cites The Cosmic Linear Anisotropy Solving System (CLASS) II: Approximation schemes.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ The Cosmic Linear Anisotropy Solving System (CLASS) II: Approximation schemes

Reference 19

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Dynamical dark energy in light of the DESI DR2 baryonic acoustic oscillations mea- surements,

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ The frontier of simulation-based inference

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This paper cites Exploring Cosmic Origins with CORE: Cosmological Parameters.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Exploring Cosmic Origins with CORE: Cosmological Parameters

Reference 22

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Efficient Computation of CMB anisotropies in closed FRW models

Reference 23

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation

Reference 24

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Implicit Likelihood Inference of the Neutrino Mass Hierarchy from Cosmological Data

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This paper cites Conservative Constraints on Early Cosmology: an illustration of the Monte Python cosmological parameter inference code.

Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Conservative Constraints on Early Cosmology: an illustration of the Monte Python cosmological parameter inference code

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Likelihood methods for the combined analysis of CMB temperature and polarisation power spectra

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ The Pantheon+ Analysis: Cosmological Constraints

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Planck 2018 results. VIII. Gravitational lensing

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ SBI -- A toolkit for simulation-based inference

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ PyTorch: An Imperative Style, High-Performance Deep Learning Library

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Masked Autoregressive Flow for Density Estimation

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Massive optimal data compression and density estimation for scalable, likelihood-free inference in cosmology

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Neural Density Estimation and Likelihood-free Inference

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Accelerated Bayesian SED Modeling using Amortized Neural Posterior Estimation

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ ${\rm S{\scriptsize IM}BIG}$: Mock Challenge for a Forward Modeling Approach to Galaxy Clustering

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ Validating Bayesian Inference Algorithms with Simulation-Based Calibration

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ emcee: The MCMC Hammer

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Implicit Likelihood Inference and $z$-Binned Reconstruction of Dark Energy $w(z)$ n1701   =L 1701   N1(0,1)

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