Experiments with expanded ensembles to explore chemical space
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Updated
Oct 28, 2025 - Python
Experiments with expanded ensembles to explore chemical space
SchNetPack - Deep Neural Networks for Atomistic Systems
End-To-End Molecular Dynamics (MD) Engine using PyTorch
NequIP is a code for building E(3)-equivariant interatomic potentials
Quantum chemistry program executor and IO standardizer (QCSchema).
Public/backup repository of the GROMACS molecular simulation toolkit. Please do not mine the metadata blindly; we use https://gitlab.com/gromacs/gromacs for code review and issue tracking.
Differentiable, Hardware Accelerated, Molecular Dynamics
Extensible Surrogate Potential of Ab initio Learned and Optimized by Message-passing Algorithm 🍹https://arxiv.org/abs/2010.01196
Message Passing Neural Networks for Molecule Property Prediction
A deep learning package for many-body potential energy representation and molecular dynamics
MaSIF- Molecular surface interaction fingerprints. Geometric deep learning to decipher patterns in molecular surfaces.
OpenMM is a toolkit for molecular simulation using high performance GPU code.
A powerful and flexible machine learning platform for drug discovery
Python package for graph neural networks in chemistry and biology
Public development project of the LAMMPS MD software package
Foundation Models for Genomics & Transcriptomics
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
The Open Free Energy toolkit
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
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