Practical Cheminformatics Tutorials

Library for Crystal Symmetry in Rust

Flow matching for accelerated simulation of atomic transport

Graph deep learning library for materials

Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

RoMa: A lightweight library to deal with 3D rotations in PyTorch.

Notebooks to follow along with "Deep Learning for Biology" Chapters 2 to 6.

Computations and statistics on manifolds with geometric structures.

This is an active learning framework that uses single-ended growing string method and neural networks to build machine learning forcefields that quickly understands reactive energy landscape.

Implementation for Flexible MOF Generation with Torsion-Aware Flow Matching

Implementation of Torsional Diffusion for Molecular Conformer Generation (NeurIPS 2022)

Inference code for scalable emulation of protein equilibrium ensembles with generative deep learning

molSimplify code

Machine Learning for HPC Workflows

Implementation for MOFFlow: Flow Matching for Structure Prediction of Metal-Organic Frameworks

A code to generate atomic structure with symmetry

Torch-native, batchable, atomistic simulations.

MACE foundation models (MP, OMAT, Matpes)

Materials science with Python at the atomic-scale

A CLI tool to convert your codebase into a single LLM prompt with source tree, prompt templating, and token counting.

SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

TorchCFM: a Conditional Flow Matching library

AlphaFold 3 inference pipeline.

Implementation of Denoising Diffusion Probabilistic Model in Pytorch

Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2

Aggregate unread emails from Google Scholar alerts

Neural Network Force Field based on PyTorch

A modular framework for neural networks with Euclidean symmetry