NequIP is a code for building E(3)-equivariant interatomic potentials
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Updated
Jun 2, 2024 - Python
NequIP is a code for building E(3)-equivariant interatomic potentials
The Open Forcefield Toolkit provides implementations of the SMIRNOFF format, parameterization engine, and other tools. Documentation available at http://open-forcefield-toolkit.readthedocs.io
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
A general cross-platform tool for preparing simulations of molecules and complex molecular assemblies
Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov
[ICLR'23 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
[ICLR'24] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
Tinker: Software Tools for Molecular Design
UF3: a python library for generating ultra-fast interatomic potentials
Build neural networks for machine learning force fields with JAX
Tinker9: Next Generation of Tinker with GPU Support
PyStokes: phoresis and Stokesian hydrodynamics in Python
KIM-based Learning-Integrated Fitting Framework for interatomic potentials.
MACE-MP models
Quantum to Molecular Mechanics (Q2MM)
Tracking citations of atomistic simulation engines
A flexible and performant framework for training machine learning potentials.
Optimization tool for calibrating coarse-grained force fields of lipids, relying on the simultaneous usage of reference AA trajectories (bottom-up) and experimental data (top-down)
A repository to hold forcefields for molecular mechanics calculations with RASPA
A dataset for benchmarking non-local capabilities of geometric machine learning models.
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