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AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification


Oct 26, 2021
Romain Egele, Romit Maulik, Krishnan Raghavan, Prasanna Balaprakash, Bethany Lusch

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Deploying deep learning in OpenFOAM with TensorFlow


Dec 01, 2020
Romit Maulik, Himanshu Sharma, Saumil Patel, Bethany Lusch, Elise Jennings

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Deep Learning Models for Global Coordinate Transformations that Linearize PDEs


Nov 07, 2019
Craig Gin, Bethany Lusch, Steven L. Brunton, J. Nathan Kutz

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* 23 pages, 18 figures 

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Using recurrent neural networks for nonlinear component computation in advection-dominated reduced-order models


Nov 01, 2019
Romit Maulik, Vishwas Rao, Sandeep Madireddy, Bethany Lusch, Prasanna Balaprakash

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Deep learning for universal linear embeddings of nonlinear dynamics


Apr 13, 2018
Bethany Lusch, J. Nathan Kutz, Steven L. Brunton

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* v2: added another example and further details (increase from 9 pages to 14 pages and increase from 4 figures to 16 figures) 

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Modeling cognitive deficits following neurodegenerative diseases and traumatic brain injuries with deep convolutional neural networks


Dec 13, 2016
Bethany Lusch, Jake Weholt, Pedro D. Maia, J. Nathan Kutz

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* 13 pages, 11 figures 

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Shape Constrained Tensor Decompositions using Sparse Representations in Over-Complete Libraries


Aug 16, 2016
Bethany Lusch, Eric C. Chi, J. Nathan Kutz

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* 12 pages, 12 figures 

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Submodular Hamming Metrics


Nov 06, 2015
Jennifer Gillenwater, Rishabh Iyer, Bethany Lusch, Rahul Kidambi, Jeff Bilmes

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* 15 pages, 1 figure, a short version of this will appear in the NIPS 2015 conference 

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