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alebrew

Official repository for the paper "Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials".

allegro

Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials

charge_transfer_nnp

Graph neural network potential with charge transfer

con-cdvae

cond-cdvae

An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]

dimenet-dgl

A DGL implementation of "Directional Message Passing for Molecular Graphs" (ICLR 2020).

dp-cdvae

Diffusion Probabilistic CDVAE

e3nn

A modular framework for neural networks with Euclidean symmetry

espaloma_charge

Standalone charge assignment from Espaloma framework.

fairchem

FAIR Chemistry's library of machine learning methods for chemistry

lammps

Compiled binaries and sources of LAMMPS, redistributed by AdvanceSoft Corp.

mace

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

matbench

Matbench: Benchmarks for materials science property prediction

matcalc

A python library for calculating materials properties

matgl

Graph deep learning library for materials

psi4numpy

Combining Psi4 and Numpy for education and development.

pymatgen

Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.

tea-workshop

torchmd-net

Neural network potentials based on graph neural networks and equivariant transformers