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Brian K. Spears

Lawrence Livermore National Laboratory, Livermore, CA

Transfer learning suppresses simulation bias in predictive models built from sparse, multi-modal data


Apr 19, 2021
Bogdan Kustowski, Jim A. Gaffney, Brian K. Spears, Gemma J. Anderson, Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan

* 13 pages, 12 figures 

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Meaningful uncertainties from deep neural network surrogates of large-scale numerical simulations


Oct 26, 2020
Gemma J. Anderson, Jim A. Gaffney, Brian K. Spears, Peer-Timo Bremer, Rushil Anirudh, Jayaraman J. Thiagarajan


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Improved Surrogates in Inertial Confinement Fusion with Manifold and Cycle Consistencies


Dec 17, 2019
Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Brian K. Spears

* 10 pages, 6 figures 

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Exploring Generative Physics Models with Scientific Priors in Inertial Confinement Fusion


Oct 03, 2019
Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer, Brian K. Spears

* Machine Learning for Physical Sciences Workshop at NeurIPS 2019 

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Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications


Jul 19, 2019
Shusen Liu, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom, Jim Gaffney, Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer


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Contemporary machine learning: a guide for practitioners in the physical sciences


Dec 20, 2017
Brian K. Spears

* 29 pages, 16 figures 

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