chemtrain: Learning Deep Potential Models via Automatic Differentiation and Statistical Physics

Documenti analoghi

• chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations
  di: Fuchs, Paul, et al.
  Pubblicazione: (2025)
• Accurate machine learning force fields via experimental and simulation data fusion
  di: Röcken, Sebastien, et al.
  Pubblicazione: (2023)
• Predicting solvation free energies with an implicit solvent machine learning potential
  di: Röcken, Sebastien, et al.
  Pubblicazione: (2024)
• Learning Non-Local Molecular Interactions via Equivariant Local Representations and Charge Equilibration
  di: Fuchs, Paul, et al.
  Pubblicazione: (2025)
• Enhanced Sampling for Efficient Learning of Coarse-Grained Machine Learning Potentials
  di: Chen, Weilong, et al.
  Pubblicazione: (2025)