π A ranked list of awesome atomistic machine learning projects βοΈπ§¬π.
β735Nov 6, 2026Updated this week
Alternatives and similar repositories for best-of-atomistic-machine-learning
Users that are interested in best-of-atomistic-machine-learning are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Torch-native, batchable, atomistic simulations.β507Updated this week
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.β1,405Oct 28, 2026Updated last week
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.β278Oct 29, 2026Updated last week
- train and use graph-based ML models of potential energy surfacesβ131Sep 22, 2026Updated last month
- A toolkit for visualizations in materials informatics.β340Updated this week
- AI Agents on DigitalOcean Gradient AI Platform β’ AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- An evaluation framework for machine learning models simulating high-throughput materials discovery.β259Updated this week
- ORB forcefield models from Orbital Materialsβ626Updated this week
- NequIP is a code for building E(3)-equivariant interatomic potentialsβ973Oct 19, 2026Updated 2 weeks ago
- A collection of Neural Network Models for chemistryβ206Oct 23, 2026Updated 2 weeks ago
- Code for automated fitting of machine learned interatomic potentials.β165Updated this week
- π [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics β¦β109Jul 2, 2026Updated 4 months ago
- FAIR Chemistry's library of machine learning methods for chemistryβ2,349Updated this week
- atomate2 is a library of computational materials science workflowsβ360Updated this week
- A python library for calculating materials properties from the PESβ157Updated this week
- Deploy on Railway without the complexity - Free Credits Offer β’ AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- GRACE models and gracemaker (as implemented in TensorPotential package)β106Oct 29, 2026Updated last week
- Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.β467Oct 26, 2026Updated last week
- quacc is a flexible platform for computational materials science and quantum chemistry that is built for the big data era.β302Updated this week
- Universal machine-learning models for advanced atomistic simulationsβ250Oct 26, 2026Updated last week
- Graph deep learning library for materialsβ580Updated this week
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIPβ¦β108Jan 28, 2026Updated 9 months ago
- [ICML'26] Phonon fine-tuning (PFT) and [NeurIPS'25 AI4Mat] Nequix: Training a foundation model for materials on a budgetβ81Apr 5, 2026Updated 7 months ago
- A code to generate atomic structure with symmetryβ394Oct 26, 2026Updated last week
- Compute neighbor lists for atomistic systemsβ89Oct 22, 2026Updated 2 weeks ago
- GPU virtual machines on DigitalOcean Gradient AI β’ AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- A Python package for estimating diffusion properties from molecular dynamics simulations.β88Oct 29, 2026Updated last week
- Package to perform automatic bonding analysis with the program Lobster in the field of computational materials science and quantum chemisβ¦β129Oct 28, 2026Updated last week
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.govβ413Sep 15, 2026Updated last month
- A Python software package for saddle point optimization and minimization of atomic systems.β189Sep 2, 2026Updated 2 months ago
- Allegro is a code for building highly scalable E(3)-equivariant interatomic potentialsβ507May 29, 2026Updated 5 months ago
- Training neural network potentialsβ486Oct 19, 2026Updated 2 weeks ago
- Interactive browser visualizations for materials science: crystal structures/molecules, trajectories, convex hulls, phase diagrams, Fermiβ¦β369Updated this week
- doped is a Python software for the generation, pre-/post-processing and analysis of defect supercell calculations, implementing the defecβ¦β285Updated this week
- Library for Crystal Symmetry in Rustβ84Updated this week
- Managed Database hosting by DigitalOcean β’ AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- MatterSim: A deep learning atomistic model across elements, temperatures and pressures.β610Updated this week
- MACE foundation models (MP, OMAT, mh-1)β324Aug 26, 2026Updated 2 months ago
- pytorch implementation of dftd2 & dftd3 (not actively maintained)β109Oct 21, 2026Updated 2 weeks ago
- An open-source Python package for creating fast and accurate interatomic potentials.β365Sep 28, 2026Updated last month
- Build neural networks for machine learning force fields with JAXβ138Jun 2, 2025Updated last year
- Some tutorial-style examples for validating machine-learned interatomic potentialsβ35Dec 4, 2023Updated 2 years ago
- Curated list of known efforts in materials informatics, i.e. in modern materials scienceβ534Mar 24, 2026Updated 7 months ago