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Picture for Ji Won Park

Ji Won Park

for the LSST Dark Energy Science Collaboration

Multi-segment preserving sampling for deep manifold sampler


May 09, 2022
Daniel Berenberg, Jae Hyeon Lee, Simon Kelow, Ji Won Park, Andrew Watkins, Vladimir Gligorijević, Richard Bonneau, Stephen Ra, Kyunghyun Cho


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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

* 6 pages, 4 figures, 1 table, written for non-astronomers, submitted to the ICML 2021 Time Series and Uncertainty and Robustness in Deep Learning Workshops. Comments welcome! Added affiliations and references for Fig 1 

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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

* 21 pages (+2 appendix), 17 figures. To be submitted to ApJ. Code at https://github.com/jiwoncpark/h0rton 

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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

* Code available at https://github.com/swagnercarena/ovejero 

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