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

Allegro is an open-source code for building highly scalable and accurate equivariant deep learning 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

Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov

[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

A general cross-platform tool for preparing simulations of molecules and complex molecular assemblies

List of molecules (small molecules, RNA, peptide, protein, enzymes, antibody, and PPIs) conformations and molecular dynamics (force fields) using generative artificial intelligence and deep learning

[ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs

MACE foundation models (MP, OMAT, mh-1)

Tinker: Software Tools for Molecular Design

Build neural networks for machine learning force fields with JAX

train and use graph-based ML models of potential energy surfaces

UF3: a python library for generating ultra-fast interatomic potentials

Tinker-GPU: Next Generation of Tinker with GPU Support

PyStokes: phoresis and Stokesian hydrodynamics in Python. github.com/rajeshrinet/pystokes

[TMLR 2024 J2C Certification] Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields

KIM-based Learning-Integrated Fitting Framework for interatomic potentials.

A flexible and performant framework for training machine learning potentials.

Tracking citations of atomistic simulation engines

Quantum to Molecular Mechanics (Q2MM)

JAX implementation of the NequIP neural network interatomic potential

A repository to hold forcefields for molecular mechanics calculations with RASPA

Interface enabling use of ANI-style, and other NN-IPs in the Amber molecular dynamics software suite. Works with both Amber engines, sander and pmemd.

Cartesian Atomic Moment Potentials -- CAMP

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 dataset for benchmarking non-local capabilities of geometric machine learning models.

Internal tool for benchmarking force fields

Cartesian Atomic Moment Potentials -- CAMP

Data and scripts relevant to an evaluation of force field methods for conformer scoring

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