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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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Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models

Oct 16, 2020
Jayaraman J. Thiagarajan, Peer-Timo Bremer, Rushil Anirudh, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz


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Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates

Oct 13, 2020
Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz


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Accurate and Robust Feature Importance Estimation under Distribution Shifts

Sep 30, 2020
Jayaraman J. Thiagarajan, Vivek Narayanaswamy, Rushil Anirudh, Peer-Timo Bremer, Andreas Spanias


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Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models

May 05, 2020
Jayaraman J. Thiagarajan, Bindya Venkatesh, Rushil Anirudh, Peer-Timo Bremer, Jim Gaffney, Gemma Anderson, Brian Spears


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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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Merlin: Enabling Machine Learning-Ready HPC Ensembles

Dec 05, 2019
J. Luc Peterson, Rushil Anirudh, Kevin Athey, Benjamin Bay, Peer-Timo Bremer, Vic Castillo, Francesco Di Natale, David Fox, Jim A. Gaffney, David Hysom, Sam Ade Jacobs, Bhavya Kailkhura, Joe Koning, Bogdan Kustowski, Steven Langer, Peter Robinson, Jessica Semler, Brian Spears, Jayaraman Thiagarajan, Brian Van Essen, Jae-Seung Yeom

* 10 pages, 5 figures; Submitted to IPDPS 2020 

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Parallelizing Training of Deep Generative Models on Massive Scientific Datasets

Oct 05, 2019
Sam Ade Jacobs, Brian Van Essen, David Hysom, Jae-Seung Yeom, Tim Moon, Rushil Anirudh, Jayaraman J. Thiagaranjan, Shusen Liu, Peer-Timo Bremer, Jim Gaffney, Tom Benson, Peter Robinson, Luc Peterson, Brian Spears


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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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Function Preserving Projection for Scalable Exploration of High-Dimensional Data

Sep 25, 2019
Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer


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Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors

Sep 09, 2019
Jayaraman J. Thiagarajan, Bindya Venkatesh, Prasanna Sattigeri, Peer-Timo Bremer


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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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A Look at the Effect of Sample Design on Generalization through the Lens of Spectral Analysis

Jun 08, 2019
Bhavya Kailkhura, Jayaraman J. Thiagarajan, Qunwei Li, Peer-Timo Bremer


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Understanding Deep Neural Networks through Input Uncertainties

Nov 01, 2018
Jayaraman J. Thiagarajan, Irene Kim, Rushil Anirudh, Peer-Timo Bremer


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Unsupervised Dimension Selection using a Blue Noise Spectrum

Oct 31, 2018
Jayaraman J. Thiagarajan, Rushil Anirudh, Rahul Sridhar, Peer-Timo Bremer


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Controlled Random Search Improves Sample Mining and Hyper-Parameter Optimization

Sep 05, 2018
Gowtham Muniraju, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Peer-Timo Bremer


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Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections

Dec 20, 2017
Jayaraman J. Thiagarajan, Shusen Liu, Karthikeyan Natesan Ramamurthy, Peer-Timo Bremer


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A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms

Dec 16, 2017
Bhavya Kailkhura, Jayaraman J. Thiagarajan, Charvi Rastogi, Pramod K. Varshney, Peer-Timo Bremer


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