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Picture for Simon Birrer

Simon Birrer

for the LSST Dark Energy Science Collaboration

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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Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era


Nov 05, 2019
Brian Nord, Andrew J. Connolly, Jamie Kinney, Jeremy Kubica, Gautaum Narayan, Joshua E. G. Peek, Chad Schafer, Erik J. Tollerud, Camille Avestruz, G. Jogesh Babu, Simon Birrer, Douglas Burke, João Caldeira, Douglas A. Caldwell, Joleen K. Carlberg, Yen-Chi Chen, Chuanfei Dong, Eric D. Feigelson, V. Zach Golkhou, Vinay Kashyap, T. S. Li, Thomas Loredo, Luisa Lucie-Smith, Kaisey S. Mandel, J. R. Martínez-Galarza, Adam A. Miller, Priyamvada Natarajan, Michelle Ntampaka, Andy Ptak, David Rapetti, Lior Shamir, Aneta Siemiginowska, Brigitta M. Sipőcz, Arfon M. Smith, Nhan Tran, Ricardo Vilalta, Lucianne M. Walkowicz, John ZuHone

* arXiv admin note: substantial text overlap with arXiv:1905.05116 

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