microsoft/mattersim

ORB forcefield models from Orbital Materials

Graph deep learning library for materials

Torch-native, batchable, atomistic simulations.

MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.

Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property constraints.

SchNetPack - Deep Neural Networks for Atomistic Systems

FAIR Chemistry's library of machine learning methods for chemistry

NequIP is a code for building E(3)-equivariant interatomic potentials