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physics.chem-ph2026
AquaGen: Scaling generative models to molecular dynamics precision on thousands of atoms
Emmanuel Bengio, Sanjeev Raja, Yui Tik Pang +5
We present AquaGen, the first all-atom, explicit solvent, periodic-boundary-condition-aware generative model that produces molecular configurations from the Boltzmann distribution…
physics.chem-ph2024
Implicit Delta Learning of High Fidelity Neural Network Potentials
Stephan Thaler, Cristian Gabellini, Nikhil Shenoy +1
Neural network potentials (NNPs) offer a fast and accurate alternative to ab-initio methods for molecular dynamics (MD) simulations but are hindered by the high cost of training da…
physics.chem-ph2024
OpenQDC: Open Quantum Data Commons
Cristian Gabellini, Nikhil Shenoy, Stephan Thaler +5
Machine Learning Interatomic Potentials (MLIPs) are a highly promising alternative to force-fields for molecular dynamics (MD) simulations, offering precise and rapid energy and fo…