ChemML

Deep learning library for Chemistry based on Tensorflow

Cross-platform library for differentiable programming of quantum computers with automatic differentiation, enabling hybrid quantum-classical machine learning for quantum chemistry, quantum physics, and NISQ algorithm research (Xanadu, 3k+ stars)

Open-source framework for building physics-ML models at scale (renamed from Modulus, 2025)

Provides functionality for producing geometric representations of protein and RNA structures, and biological interaction networks.

E(3)-equivariant neural network interatomic potentials achieving DFT accuracy with up to 1000× less training data than invariant models, foundational architecture behind MACE and Allegro (Harvard, MIT, Nature Communications 2022)

OpenChem is a deep learning toolkit for Computational Chemistry with PyTorch backend.