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Aaron Roodman

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for the LSST Dark Energy Science Collaboration

Hierarchical Inference of the Lensing Convergence from Photometric Catalogs with Bayesian Graph Neural Networks

Nov 15, 2022
Ji Won Park, Simon Birrer, Madison Ueland, Miles Cranmer, Adriano Agnello, Sebastian Wagner-Carena, Philip J. Marshall, Aaron Roodman, the LSST Dark Energy Science Collaboration

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Inferring Black Hole Properties from Astronomical Multivariate Time Series with Bayesian Attentive Neural Processes

Jun 18, 2021
Ji Won Park, Ashley Villar, Yin Li, Yan-Fei Jiang, Shirley Ho, Joshua Yao-Yu Lin, Philip J. Marshall, Aaron Roodman

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Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant

Nov 30, 2020
Ji Won Park, Sebastian Wagner-Carena, Simon Birrer, Philip J. Marshall, Joshua Yao-Yu Lin, Aaron Roodman

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Hierarchical Inference With Bayesian Neural Networks: An Application to Strong Gravitational Lensing

Oct 28, 2020
Sebastian Wagner-Carena, Ji Won Park, Simon Birrer, Philip J. Marshall, Aaron Roodman, Risa H. Wechsler

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