A deep learning package for many-body potential energy representation and molecular dynamics
-
Updated
Jul 29, 2026 - Python
A deep learning package for many-body potential energy representation and molecular dynamics
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
End-To-End Molecular Dynamics (MD) Engine using PyTorch
NequIP is a code for building E(3)-equivariant interatomic potentials
OpenMM plugin to define forces with neural networks
High level API for using machine learning models in OpenMM simulations
Differentiable, Hardware Accelerated, Molecular Dynamics
To associate your repository with the task-ml-potential topic, visit your repo's landing page and select "manage topics."