47 citations · 194 across the 10 of their papers we have counts for
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physics.chem-ph2025★ 1 cited
Accelerating Molecular Dynamics Simulations with Foundation Neural Network Models using Multiple Time-Step and Distillation
Côme Cattin, Thomas Plé, Olivier Adjoua +3
We present a distilled multi-time-step (DMTS) strategy to accelerate molecular dynamics simulations using foundation neural network models. DMTS uses a dual-level neural network wh…
physics.chem-ph2025★ 2 cited
The Q-AMOEBA (CF) Polarizable Potential
Nastasia Mauger, Thomas Plé, Louis Lagardère +2
We present Q-AMOEBA (CF), an enhanced version of the Q-AMOEBA polarizable model that integrates a geometry-dependent charge flux (CF) term while designed for an explicit treatment…