191 citations · 384 across the 10 of their papers we have counts for
3 papers · 1 filter
Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant
Ji Won Park, Sebastian Wagner-Carena, Simon Birrer +3
We investigate the use of approximate Bayesian neural networks (BNNs) in modeling hundreds of time-delay gravitational lenses for Hubble constant () determination. Our BNN was…
Hierarchical Inference With Bayesian Neural Networks: An Application to Strong Gravitational Lensing
Sebastian Wagner-Carena, Ji Won Park, Simon Birrer +3
In the past few years, approximate Bayesian Neural Networks (BNNs) have demonstrated the ability to produce statistically consistent posteriors on a wide range of inference problem…
The LSST DESC DC2 Simulated Sky Survey
LSST Dark Energy Science Collaboration, Bela Abolfathi, David Alonso +77
We describe the simulated sky survey underlying the second data challenge (DC2) carried out in preparation for analysis of the Vera C. Rubin Observatory Legacy Survey of Space and…