Neural Posterior Estimation for Inferring Weak Lensing Shear
Tim White, Dingrui Tao, Camille Avestruz, Jeffrey Regier, the LSST Dark Energy Science Collaboration
astro-ph.IM, astro-ph.CO, cs.CV, stat.AP
Submitted: 2026-07-10
Comments: 17 pages, 10 figures, 3 tables
Code: https://github.com/mr-superonion/AnaCal
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- DESC DC2 Data Release Note
- The Wide Field Infrared Survey Telescope: 100 Hubbles for the 2020s
- Forward Amortized Inference for Likelihood-Free Variational Marginalization
- The little coadd that could: Estimating shear from coadded images
- Investigating the Impact of Model Misspecification in Neural Simulation-based Inference
- CoLT: The conditional localization test for assessing the accuracy of neural posterior estimates
- WFIRST: The Essential Cosmology Space Observatory for the Coming Decade
- The Statistical Accuracy of Neural Posterior and Likelihood Estimation
- Deep Residual Learning for Image Recognition
- A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful
- Simulation-based Bayesian inference under model misspecification
- Euclid Definition Study Report
- The LSST Dark Energy Science Collaboration (DESC) Science Requirements Document
- Differentiable Forward Modeling for Efficient and Accurate Shear Inference
- Metadetection Weak Lensing for the Vera C. Rubin Observatory
- Wide-Field InfrarRed Survey Telescope-Astrophysics Focused Telescope Assets WFIRST-AFTA 2015 Report
- Validating Bayesian Inference Algorithms with Simulation-Based Calibration
- Group Normalization
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