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AGNet: Weighing Black Holes with Deep Learning

Aug 17, 2021
Joshua Yao-Yu Lin, Sneh Pandya, Devanshi Pratap, Xin Liu, Matias Carrasco Kind, Volodymyr Kindratenko

* 8 pages, 7 figures, 1 table, submitting to MNRAS 

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AGNet: Weighing Black Holes with Machine Learning

Dec 01, 2020
Joshua Yao-Yu Lin, Sneh Pandya, Devanshi Pratap, Xin Liu, Matias Carrasco Kind

* 5 pages, 3 figures, 1 table. Accepted to the Machine Learning and the Physical Sciences Workshop at NeurIPS 2020 

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Survey2Survey: A deep learning generative model approach for cross-survey image mapping

Nov 13, 2020
Brandon Buncher, Awshesh Nath Sharma, Matias Carrasco Kind

* 13 pages, 18 figures 

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Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era

Feb 01, 2019
Gabrielle Allen, Igor Andreoni, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Daniel George, Tom Gibbs, Matthew Graham, William Gropp, Anushri Gupta, Roland Haas, E. A. Huerta, Elise Jennings, Daniel S. Katz, Asad Khan, Volodymyr Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Kenton McHenry, J. M. Miller, M. S. Neubauer, Steve Oberlin, Alexander R. Olivas Jr, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard Schutz, Alex Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Brigitta M. Sipőcz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao

* 15 pages, no figures. White paper based on the "Deep Learning for Multi-Messenger Astrophysics: Real-time Discovery at Scale" workshop, hosted at NCSA, October 17-19, 2018 

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Extended Isolation Forest

Nov 06, 2018
Sahand Hariri, Matias Carrasco Kind, Robert J. Brunner

* 11 pages; 21 figures 

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