203 citations · 464 across the 9 of their papers we have counts for
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physics.chem-ph2021
Improving Molecular Force Fields Across Configurational Space by Combining Supervised and Unsupervised Machine Learning
Gregory Fonseca, Igor Poltavsky, Valentin Vassilev-Galindo +1
The training set of atomic configurations is key to the performance of any Machine Learning Force Field (MLFF) and, as such, the training set selection determines the applicability…
physics.chem-ph2021★ 52 cited
Challenges for Machine Learning Force Fields in Reproducing Potential Energy Surfaces of Flexible Molecules
Valentin Vassilev-Galindo, Gregory Fonseca, Igor Poltavsky +1
Dynamics of flexible molecules are often determined by an interplay between local chemical bond fluctuations and conformational changes driven by long-range electrostatics and van…