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Machine-learning Kondo physics using variational autoencoders


Jul 16, 2021
Cole Miles, Matthew R. Carbone, Erica J. Sturm, Deyu Lu, Andreas Weichselbaum, Kipton Barros, Robert M. Konik

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* 9 pages + 5 pages appendix, 14 figures 

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Simple and efficient algorithms for training machine learning potentials to force data


Jun 09, 2020
Justin S. Smith, Nicholas Lubbers, Aidan P. Thompson, Kipton Barros

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Automated discovery of a robust interatomic potential for aluminum


Mar 10, 2020
Justin S. Smith, Benjamin Nebgen, Nithin Mathew, Jie Chen, Nicholas Lubbers, Leonid Burakovsky, Sergei Tretiak, Hai Ah Nam, Timothy Germann, Saryu Fensin, Kipton Barros

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Hierarchical modeling of molecular energies using a deep neural network


Sep 29, 2017
Nicholas Lubbers, Justin S. Smith, Kipton Barros

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Inferring low-dimensional microstructure representations using convolutional neural networks


Nov 08, 2016
Nicholas Lubbers, Turab Lookman, Kipton Barros

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* Phys. Rev. E 96, 052111 (2017) 
* 25 Pages, 12 Figures 

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