janosh/matbench-discovery

Graph deep learning library for materials

Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov

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

FAIR Chemistry's library of machine learning methods for chemistry

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

Code for automated fitting of machine learned interatomic potentials.

MACE foundation models (MP, OMAT, mh-1)

🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.