Emerging Trends in Molecular Dynamics Simulations and Machine Learning IV
FOCUS · N60 · ID: 1067988
Presentations
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Refinement of Training Schemes for Machine-Learning Interatomic Potentials and Its Applications
ORAL · Invited
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Presenters
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Kohei Shimamura
Kumamoto University
Authors
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Kohei Shimamura
Kumamoto University
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Benchmarking machine-learned interatomic potential methods for reactive molecular dynamics at metal surfaces
ORAL
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Presenters
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Wojciech G Stark
University of Warwick
Authors
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Wojciech G Stark
University of Warwick
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Julia Westermayr
University of Warwick
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Cas van der Oord
University of Cambridge
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Gabor Csanyi
University of Cambridge
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Reinhard J Maurer
University of Warwick
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Fast and Scalable Uncertainty Estimates in Deep Learning Interatomic Potentials
ORAL
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Presenters
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Albert Zhu
Harvard University
Authors
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Albert Zhu
Harvard University
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Simon L Batzner
Harvard University
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Albert Musaelian
Harvard University
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Boris Kozinsky
Harvard University
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Predicting Vapor-Liquid Equilibria and Phase Transitions with Machine-Learned Interatomic Potentials
ORAL
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Presenters
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Dionysios Sema
Sandia National Laboratories, Massachusetts Institute of Technology
Authors
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Mitchell A Wood
Sandia National Laboratories
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Normand A Modine
Sandia National Laboratories
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Dionysios Sema
Sandia National Laboratories, Massachusetts Institute of Technology
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Ember Sikorski
Sandia National Labs
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Stan Moore
Sandia National Lab
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Nicolas G Hadjiconstantinou
MIT Lincoln Lab
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Numerical modeling of hydrogen absorption in metal hydrides
ORAL
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Presenters
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Olivier Nadeau
Université du Québec à Trois-Rivières (UQTR)
Authors
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Olivier Nadeau
Université du Québec à Trois-Rivières (UQTR)
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Gabriel Antonius
Université du Québec à Trois-Rivières (UQTR), Université du Québec à Trois-Rivières
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