activity
20192025
most citedLearning neural network potentials from experimental data via Differentiable Trajectory Reweighting

112 citations · 215 across the 7 of their papers we have counts for

collaborators
Showing 2025 · physics.comp-phShow all

1 paper · 2 filters

physics.comp-ph2025

chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations

Paul Fuchs, Weilong Chen, Stephan Thaler +1

Machine learning potentials (MLPs) have advanced rapidly and show great promise to transform molecular dynamics (MD) simulations. However, most existing software tools are tied to…