Build neural networks for machine learning force fields with JAX
☆133Jun 2, 2025Updated 9 months ago
Alternatives and similar repositories for mlff
Users that are interested in mlff are comparing it to the libraries listed below
Sorting:
- E3x is a JAX library for constructing efficient E(3)-equivariant deep learning architectures built on top of Flax.☆111Apr 7, 2025Updated 10 months ago
- SO3krates and Universal Pairwise Force Field for Molecular Simulation☆203Feb 16, 2026Updated 2 weeks ago
- ☆23Nov 1, 2023Updated 2 years ago
- An implementation of SchNet in JAX and JAX-MD.☆17Apr 5, 2022Updated 3 years ago
- jax library for E3 Equivariant Neural Networks☆224Aug 25, 2025Updated 6 months ago
- A collection of files related to machine learning force fields☆22Oct 25, 2023Updated 2 years ago
- tools for graph-based machine-learning potentials in jax☆26Apr 9, 2024Updated last year
- JAX implementation of the NequIP neural network interatomic potential☆16Feb 24, 2026Updated last week
- Implementation of the Euclidean fast attention (EFA) algorithm☆61Jan 7, 2026Updated last month
- ☆120Feb 10, 2026Updated 3 weeks ago
- Compute neighbor lists for atomistic systems☆74Updated this week
- Equivariant machine learning interatomic potentials in JAX.☆87Feb 10, 2026Updated 3 weeks ago
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆226Feb 25, 2026Updated last week
- AIMNet2: Fast, accurate and transferable neural network interatomic potential☆18Oct 17, 2024Updated last year
- NequIP is a code for building E(3)-equivariant interatomic potentials☆868Feb 25, 2026Updated last week
- OMNI-P2x: A universal neural network potential for excited states☆12Updated this week
- Training neural network potentials☆468Feb 25, 2026Updated last week
- The FPTE package is a collection of tools for finite pressure temperature elastic constants calculation. Features include, but are not l…☆17Jan 19, 2025Updated last year
- Torch-native C++/CUDA library to accelerate tensor-product layers in MLIPs☆55Nov 26, 2025Updated 3 months ago
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆96Jan 28, 2026Updated last month
- Collection of tutorials to use the MACE machine learning force field.☆53Jan 22, 2026Updated last month
- Computing representations for atomistic machine learning☆78Feb 4, 2026Updated last month
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.☆1,064Feb 23, 2026Updated last week
- A library for building equivariant neural networks and a zoo of implementations & examples.☆31Aug 9, 2022Updated 3 years ago
- Reference implementation of "Ewald-based Long-Range Message Passing for Molecular Graphs" (ICML 2023)☆53Jun 13, 2023Updated 2 years ago
- scalable molecular simulation☆140Oct 13, 2025Updated 4 months ago
- [TMLR 2023] Training and simulating MD with ML force fields☆115Oct 30, 2024Updated last year
- train and use graph-based ML models of potential energy surfaces☆122Feb 20, 2026Updated last week
- Software for generating machine-learning interatomic potentials for LAMMPS☆182Oct 17, 2025Updated 4 months ago
- ☆22May 7, 2025Updated 9 months ago
- Multi-language library for the calculation of spherical harmonics in Cartesian coordinates☆94Feb 17, 2026Updated 2 weeks ago
- High-performance operations for neural network potentials☆102Feb 4, 2026Updated last month
- An overview of literature that discusses the use of machine learning for atomistic simulations☆44Apr 11, 2023Updated 2 years ago
- Description, readme and source-files for crystIT, a python based program to calculated complexity measures for crystal structures based o…☆16Dec 24, 2025Updated 2 months ago
- A framework for performing active learning for training machine-learned interatomic potentials.☆39Nov 10, 2025Updated 3 months ago
- A flexible and performant framework for training machine learning potentials.☆35Feb 24, 2026Updated last week
- Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials☆463Feb 23, 2026Updated last week
- An interactive structure/property explorer for materials and molecules☆173Feb 23, 2026Updated last week
- ☆13Dec 14, 2024Updated last year