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

SchNetPack - Deep Neural Networks for Atomistic Systems

Extensible Surrogate Potential of Ab initio Learned and Optimized by Message-passing Algorithm 🍹https://arxiv.org/abs/2010.01196

Differentiable, Hardware Accelerated, Molecular Dynamics

NequIP is a code for building E(3)-equivariant interatomic potentials

High level API for using machine learning models in OpenMM simulations

OpenMM plugin to define forces with neural networks

A deep learning package for many-body potential energy representation and molecular dynamics