191 citations · 223 across the 3 of their papers we have counts for
5 papers
Hierarchical Inference of the Lensing Convergence from Photometric Catalogs with Bayesian Graph Neural Networks
Ji Won Park, Simon Birrer, Madison Ueland +6
We present a Bayesian graph neural network (BGNN) that can estimate the weak lensing convergence () from photometric measurements of galaxies along a given line of sight. The me…
lenstronomy II: A gravitational lensing software ecosystem
Simon Birrer, Anowar J. Shajib, Daniel Gilman +18
lenstronomy is an Astropy-affiliated Python package for gravitational lensing simulations and analyses. lenstronomy was introduced by Birrer and Amara (2018) and is based on the li…
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…
TDCOSMO IV: Hierarchical time-delay cosmography -- joint inference of the Hubble constant and galaxy density profiles
S. Birrer, A. J. Shajib, A. Galan +24
The H0LiCOW collaboration inferred via gravitational lensing time delays a Hubble constant km s, describing deflector mass density pro…