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Data-driven interatomic potentials have emerged as a powerful class of surrogate models for {\it ab initio} potential energy surfaces that are able to reliably predict macroscopic properties with experimental accuracy.
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Bastiaan J. Braams and Joel M. Bowman · 2009
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Albert P. Bartók, Mike C. Payne, Risi Kondor, and Gábor Csányi · 2010
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Eric Brochu, Vlad M Cora, and Nando De Freitas · 2010
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John Wiley and Sons, Ltd, 2012
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Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials
A.P. Thompson, L.P. Swiler, C.R. Trott, S.M. Foiles, and G.J. Tucker · 2015
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Gaussian approximation potentials: A brief tutorial introduction
Albert P Bartók and Gábor Csányi · 2015
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Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials
Aidan P Thompson, Laura P Swiler, Christian R Trott, Stephen M Foiles, and Garritt J Tucker · 2015
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Moment tensor potentials: A class of systematically improvable interatomic potentials
Alexander V. Shapeev · 2016
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Robert JN Baldock, Lívia B Pártay, Albert P Bartók, Michael C Payne, and Gábor Csányi · 2016
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Ming Tang, P. Chris Pistorius, Sneha Narra, and Jack L. Beuth · 2016
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ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost
J. S. Smith, O. Isayev, and A. E. Roitberg · 2017
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Albert P. Bartók, Sandip De, Carl Poelking, Noam Bernstein, James R. Kermode, Gábor Csányi, and Michele Ceriotti · 2017
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Kristof T. Schütt, Farhad Arbabzadah, Stefan Chmiela, Klaus R. Müller, and Alexandre Tkatchenko · 2017
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Active learning of linearly parametrized interatomic potentials
Evgeny V. Podryabinkin and Alexander V. Shapeev · 2017
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Volker L. Deringer, Miguel A. Caro, and Gábor Csányi · 2020
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Machine-learned interatomic potentials by active learning: amorphous and liquid hafnium dioxide
Ganesh Sivaraman, Anand Narayanan Krishnamoorthy, Matthias Baur, Christian Holm, Marius Stan, Gábor Csányi, Chris Benmore, and Álvaro Vázquez-Mayagoitia · 2020
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Han Wang, Linfeng Zhang, Jiequn Han, and Weinan E · 2018
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Han Wang, Linfeng Zhang, Jiequn Han, and Weinan E · 2018
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Machine learning a general-purpose interatomic potential for silicon
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Maximizing acquisition functions for bayesian optimization, 2018
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