Message Passing Neural Networks for Molecule Property Prediction

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

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…

FAIR Chemistry's library of machine learning methods for chemistry

Generic template to bootstrap your PyTorch project.

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

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

Machine Learning on Google Cloud Platform

The official repository for the AiiDA code

Molecular De Novo design using Recurrent Neural Networks and Reinforcement Learning

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

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

Implementation of E(n)-Transformer, which incorporates attention mechanisms into Welling's E(n)-Equivariant Graph Neural Network

atomate2 is a library of computational materials science workflows

Molecule Design using Monte Carlo Tree Search with Neural Rollout