Multiscale Modeling of Fluid Materials

Training Neural Network potentials through customizable routines in JAX.

Code for the paper “Refining machine learning potentials through thermodynamic theory of phase transitions.”

[ICML 2026] Coarse-Grained Boltzmann Generators

PepMorph, an end-to-end peptide discovery pipeline for morphology-aware novel sequence generation

Testing different CG mappings with classical and machine learning potentials.

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

Charge Equilibration for Long-Range Interactions