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Anomaly Detection for Multivariate Time Series of Exotic Supernovae

Oct 21, 2020
V. Ashley Villar, Miles Cranmer, Gabriella Contardo, Shirley Ho, Joshua Yao-Yu Lin

* 6 pages, 2 figures, written for non-astronomers, submitted to the NeurIPS workshop Machine Learning and the Physical Sciences. Comments welcome!! 

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Meta-Learning One-Class Classification with DeepSets: Application in the Milky Way

Jul 08, 2020
Ademola Oladosu, Tony Xu, Philip Ekfeldt, Brian A. Kelly, Miles Cranmer, Shirley Ho, Adrian M. Price-Whelan, Gabriella Contardo


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Discovering Symbolic Models from Deep Learning with Inductive Biases

Jun 19, 2020
Miles Cranmer, Alvaro Sanchez-Gonzalez, Peter Battaglia, Rui Xu, Kyle Cranmer, David Spergel, Shirley Ho

* 9 pages content + 14 pages appendix/references. Supporting code found at https://github.com/MilesCranmer/symbolic_deep_learning 

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Lagrangian Neural Networks

Mar 10, 2020
Miles Cranmer, Sam Greydanus, Stephan Hoyer, Peter Battaglia, David Spergel, Shirley Ho

* 7 pages (+2 appendix). Accepted to ICLR 2020 Deep Differential Equations Workshop. Code at github.com/MilesCranmer/lagrangian_nns 

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From Dark Matter to Galaxies with Convolutional Neural Networks

Oct 17, 2019
Jacky H. T. Yip, Xinyue Zhang, Yanfang Wang, Wei Zhang, Yueqiu Sun, Gabriella Contardo, Francisco Villaescusa-Navarro, Siyu He, Shy Genel, Shirley Ho

* 5 pages, 2 figures. Accepted to the Second Workshop on Machine Learning and the Physical Sciences (NeurIPS 2019) 

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Learning neutrino effects in Cosmology with Convolutional Neural Networks

Oct 09, 2019
Elena Giusarma, Mauricio Reyes Hurtado, Francisco Villaescusa-Navarro, Siyu He, Shirley Ho, ChangHoon Hahn

* 8 pages, 7 figures 

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Learning Symbolic Physics with Graph Networks

Sep 12, 2019
Miles D. Cranmer, Rui Xu, Peter Battaglia, Shirley Ho

* 5 pages; 3 figures; submitted to Machine Learning and the Physical Sciences Workshop @ NeurIPS 2019 

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Modeling the Gaia Color-Magnitude Diagram with Bayesian Neural Flows to Constrain Distance Estimates

Aug 21, 2019
Miles D. Cranmer, Richard Galvez, Lauren Anderson, David N. Spergel, Shirley Ho

* 15 pages, 8 figures 

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HIGAN: Cosmic Neutral Hydrogen with Generative Adversarial Networks

Apr 29, 2019
Juan Zamudio-Fernandez, Atakan Okan, Francisco Villaescusa-Navarro, Seda Bilaloglu, Asena Derin Cengiz, Siyu He, Laurence Perreault Levasseur, Shirley Ho

* 9 pages, 8 figures 

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From Dark Matter to Galaxies with Convolutional Networks

Apr 01, 2019
Xinyue Zhang, Yanfang Wang, Wei Zhang, Yueqiu Sun, Siyu He, Gabriella Contardo, Francisco Villaescusa-Navarro, Shirley Ho

* 10 pages, 11 figures, submitted for KDD 2019 

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Learning to Predict the Cosmological Structure Formation

Nov 15, 2018
Siyu He, Yin Li, Yu Feng, Shirley Ho, Siamak Ravanbakhsh, Wei Chen, Barnabás Póczos

* 7 pages, 5 figures, 1 table 

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CosmoFlow: Using Deep Learning to Learn the Universe at Scale

Aug 14, 2018
Amrita Mathuriya, Deborah Bard, Peter Mendygral, Lawrence Meadows, James Arnemann, Lei Shao, Siyu He, Tuomas Karna, Daina Moise, Simon J. Pennycook, Kristyn Maschoff, Jason Sewall, Nalini Kumar, Shirley Ho, Mike Ringenburg, Prabhat, Victor Lee

* 12 pages, 6 pages, accepted to SuperComputing 2018 

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Estimating Cosmological Parameters from the Dark Matter Distribution

Nov 06, 2017
Siamak Ravanbakhsh, Junier Oliva, Sebastien Fromenteau, Layne C. Price, Shirley Ho, Jeff Schneider, Barnabas Poczos

* ICML 2016 

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Optimal Ridge Detection using Coverage Risk

Jun 07, 2015
Yen-Chi Chen, Christopher R. Genovese, Shirley Ho, Larry Wasserman

* 16 pages, 4 figures 

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