Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property c…

atomate2 is a library of computational materials science workflows

Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.

higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual training steps.

FAIR Chemistry's library of machine learning methods for chemistry

Generic template to bootstrap your PyTorch project.

code for the SE3 Transformers paper: https://arxiv.org/abs/2006.10503

End-To-End Molecular Dynamics (MD) Engine using PyTorch

Message Passing Neural Networks for Molecule Property Prediction

The official repository for the AiiDA code

OpenMM is a toolkit for molecular simulation using high performance GPU code.

Machine Learning on Google Cloud Platform

Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.

Molecular De Novo design using Recurrent Neural Networks and Reinforcement Learning

Molecule Design using Monte Carlo Tree Search with Neural Rollout

Gaussian Process Optimization using GPy

Deep learning meets molecular dynamics.

📐 Jekyll theme for building a personal site, blog, project documentation, or portfolio.