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

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

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

[ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs

A Python library and command line interface for automated free energy calculations

python library for atomistic machine learning

Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIPs). It offers a growing set of evaluation methods alongside powerful visualization and comparison tools.

UF3: a python library for generating ultra-fast interatomic potentials

Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics

KIM-based Learning-Integrated Fitting Framework for interatomic potentials.

A flexible and performant framework for training machine learning potentials.

Fitting interatomic potential for molecular dynamics

A Python library for developing machine learning interatomic potentials, based on JAX.

A python package for fast building amorphous solids and liquid mixtures from @materialsproject computed structures and machine learning interatomic potentials

A parallel molecular dynamics simulation algorithm for studying the thermal stability of nanoalloys.

Сollection of ab initio calculated molecular potential energy surfaces

An attempt to fit ab-initio materials database (e.g. Materials Project) results to FitSNAP potential.

Impliment of the ReaxFF-nn mathine learning potential in the GULP package