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cs.LG2026
A budget-dependent crossover between coverage- and response-based training-set selection for machine-learned interatomic potentials
Jia Bi, Alin-Marin Elena
Selecting compact training sets for machine-learned interatomic potentials requires deciding whether to preserve structural diversity or target configurations on which models disag…
cs.LG2026
Scalar-pathway fidelity improves physical accuracy in short-range equivariant interatomic potentials
Jia Bi, Alin Marin Elena, Samuel Pinilla
Accurate interatomic potentials enable molecular dynamics of materials, molecules, and interfaces beyond density-functional-theory length and time scales. Equivariant neural networ…