10 citations · 17 across the 4 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cond-mat.mtrl-sci2023
Exploring Model Complexity in Machine Learned Potentials for Simulated Properties
Andrew Rohskopf, James Goff, Dionysios Sema +5
Machine learning (ML) enables the development of interatomic potentials that promise the accuracy of first principles methods while retaining the low cost and parallel efficiency o…
physics.chem-ph2023★ 10 cited
Shadow molecular dynamics and atomic cluster expansions for flexible charge models
James Goff, Yu Zhang, Christian F. A. Negre +2
A shadow molecular dynamics scheme for flexible charge models is presented, where the shadow Born-Oppenheimer potential is derived from a coarse-grained approximation of range-sepa…