orbital-materials/orb-models

MatterSim: A deep learning atomistic model across elements, temperatures and pressures.

Torch-native, batchable, atomistic simulations.

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

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

SchNetPack - Deep Neural Networks for Atomistic Systems

Graph deep learning library for materials

FAIR Chemistry's library of machine learning methods for chemistry

TorchANI 2.0 is an open-source library that supports training, development, and research of ANI-style neural network interatomic potentials. It was originally developed and is currently maintained by the Roitberg group.

A deep learning package for many-body potential energy representation and molecular dynamics