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

Code for automated fitting of machine learned interatomic potentials.

A machine learning environment for atomic-scale modeling in surface science and catalysis.

python library for atomistic machine learning

An open-source active learning framework for training machine-learned interatomic potentials

Library for handling atomistic graph datasets focusing on transformer-based implementations, with utilities for training various models, experimenting with different pre-training tasks, and a suite of pre-trained models with huggingface integrations

ConfRank+: Extending Conformer Ranking to Charged Molecules

This repository connects AniSOAP descriptors to ASE energy models through an explicit calculator interface, with optional finite-difference forces. It was developed during Fall 2025 OSPO internship with the Cersonsky Lab at UW–Madison.

SchNetPack - Deep Neural Networks for Atomistic Systems

This repository documents a DOI-backed profiling and optimization study of AniSOAP's NumPy and PyTorch descriptor pipelines across CPU and Apple MPS. It was developed during Fall 2025 OSPO internship with the Cersonsky Lab at UW–Madison. It's maintained successor is AniSOAP-Torch.