SchNetPack - Deep Neural Networks for Atomistic Systems
-
Updated
Jul 28, 2026 - Python
SchNetPack - Deep Neural Networks for Atomistic Systems
OpenMM plugin to define forces with neural networks
High level API for using machine learning models in OpenMM simulations
End-To-End Molecular Dynamics (MD) Engine using PyTorch
NequIP is a code for building E(3)-equivariant interatomic potentials
Differentiable, Hardware Accelerated, Molecular Dynamics
Extensible Surrogate Potential of Ab initio Learned and Optimized by Message-passing Algorithm 🍹https://arxiv.org/abs/2010.01196
A deep learning package for many-body potential energy representation and molecular dynamics
Add a description, image, and links to the task-ml-potential topic page so that developers can more easily learn about it.
To associate your repository with the task-ml-potential topic, visit your repo's landing page and select "manage topics."