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physics.comp-ph2025
Distillation of atomistic foundation models across architectures and chemical domains
John L. A. Gardner, Daniel F. Thomas du Toit, Chiheb Ben Mahmoud +8
Machine-learned interatomic potentials have transformed computational research in the physical sciences. Recent atomistic `foundation' models have changed the field yet again: trai…
physics.comp-ph2025
Force-Free Molecular Dynamics Through Autoregressive Equivariant Networks
Fabian L. Thiemann, Thiago Reschützegger, Massimiliano Esposito +3
Molecular dynamics (MD) simulations play a crucial role in scientific research. Yet their computational cost often limits the timescales and system sizes that can be explored. Most…