Equivariant machine learning interatomic potentials in JAX.

The UppASD package is a simulation tool for atomistic spin dynamics and Monte Carlo simulations of Heisenberg spin systems.

FAIR Chemistry's library of machine learning methods for chemistry

Open-Source Quantum Chemistry – an electronic structure package in C++ driven by Python

A JAX library for Density Functional Theory.

[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

GradDFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation functionals using machine learning techniques.

This repository is built to collect the background of the machine learning and AI techniques for density functional theory (DFT).