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Learning from learning machines: a new generation of AI technology to meet the needs of science


Nov 27, 2021
Luca Pion-Tonachini, Kristofer Bouchard, Hector Garcia Martin, Sean Peisert, W. Bradley Holtz, Anil Aswani, Dipankar Dwivedi, Haruko Wainwright, Ghanshyam Pilania, Benjamin Nachman, Babetta L. Marrone, Nicola Falco, Prabhat, Daniel Arnold, Alejandro Wolf-Yadlin, Sarah Powers, Sharlee Climer, Quinn Jackson, Ty Carlson, Michael Sohn, Petrus Zwart, Neeraj Kumar, Amy Justice, Claire Tomlin, Daniel Jacobson, Gos Micklem, Georgios V. Gkoutos, Peter J. Bickel, Jean-Baptiste Cazier, Juliane Müller, Bobbie-Jo Webb-Robertson, Rick Stevens, Mark Anderson, Ken Kreutz-Delgado, Michael W. Mahoney, James B. Brown

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Track Seeding and Labelling with Embedded-space Graph Neural Networks


Jun 30, 2020
Nicholas Choma, Daniel Murnane, Xiangyang Ju, Paolo Calafiura, Sean Conlon, Steven Farrell, Prabhat, Giuseppe Cerati, Lindsey Gray, Thomas Klijnsma, Jim Kowalkowski, Panagiotis Spentzouris, Jean-Roch Vlimant, Maria Spiropulu, Adam Aurisano, Jeremy Hewes, Aristeidis Tsaris, Kazuhiro Terao, Tracy Usher

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* Proceedings submission in Connecting the Dots Workshop 2020, 10 pages 

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MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework


May 01, 2020
Chiyu Max Jiang, Soheil Esmaeilzadeh, Kamyar Azizzadenesheli, Karthik Kashinath, Mustafa Mustafa, Hamdi A. Tchelepi, Philip Marcus, Prabhat, Anima Anandkumar

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* Supplementary Video: https://youtu.be/mjqwPch9gDo 

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Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs


Oct 29, 2019
Liu Yang, Sean Treichler, Thorsten Kurth, Keno Fischer, David Barajas-Solano, Josh Romero, Valentin Churavy, Alexandre Tartakovsky, Michael Houston, Prabhat, George Karniadakis

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* 3rd Deep Learning on Supercomputers Workshop (DLS) at SC19 

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DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems


Sep 25, 2019
Adam Rupe, Nalini Kumar, Vladislav Epifanov, Karthik Kashinath, Oleksandr Pavlyk, Frank Schlimbach, Mostofa Patwary, Sergey Maidanov, Victor Lee, Prabhat, James P. Crutchfield

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Towards Unsupervised Segmentation of Extreme Weather Events


Sep 16, 2019
Adam Rupe, Karthik Kashinath, Nalini Kumar, Victor Lee, Prabhat, James P. Crutchfield

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Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale


Jul 08, 2019
Atılım Güneş Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip Torr, Victor Lee, Kyle Cranmer, Prabhat, Frank Wood

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* 14 pages, 8 figures 

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Enforcing Statistical Constraints in Generative Adversarial Networks for Modeling Chaotic Dynamical Systems


May 13, 2019
Jin-Long Wu, Karthik Kashinath, Adrian Albert, Dragos Chirila, Prabhat, Heng Xiao

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Spherical CNNs on Unstructured Grids


Jan 07, 2019
Chiyu "Max" Jiang, Jingwei Huang, Karthik Kashinath, Prabhat, Philip Marcus, Matthias Niessner

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* Accepted as a conference paper at ICLR 2019. Codes available at https://github.com/maxjiang93/ugscnn 

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Approximate Inference for Constructing Astronomical Catalogs from Images


Oct 12, 2018
Jeffrey Regier, Andrew C. Miller, David Schlegel, Ryan P. Adams, Jon D. McAuliffe, Prabhat

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* major revision for AoAS 

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