JinukMoon/CatBench

ML Performance and Extrapolation Guide (reference deployment https://ml-peg.stfc.ac.uk)

An evaluation framework for machine learning models simulating high-throughput materials discovery.

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

Generating Deep Potential with Python

Code for automated fitting of machine learned interatomic potentials.

Library for efficient training and application of Machine Learning Interatomic Potentials (MLIP)

train and use graph-based ML models of potential energy surfaces

FAIR Chemistry's library of machine learning methods for chemistry