JuDFTteam/best-of-atomistic-machine-learning GitHub

🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.

Best of Atomistic Machine Learning ⚛️🧬💎
  

















🏆&nbsp; A ranked list of awesome atomistic machine learning (AML) projects. Updated regularly.





[![](http://bit.ly/3o3EHNN)](https://best-of.org)
[![](https://img.shields.io/badge/projects-520-blue.svg?color=5ac4bf)](#Contents)
[![](https://img.shields.io/badge/contributions-welcome-green.svg)](#Contribution)
[![](https://img.shields.io/github/release-date/JuDFTteam/best-of-atomistic-machine-learning?color=green&label=updated)](https://github.com/JuDFTteam/best-of-atomistic-machine-learning/releases)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10430261.svg)](https://doi.org/10.5281/zenodo.10430261)

This curated list contains 520 awesome open-source projects with a total of 250K stars grouped into 23 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml.

The current focus of this list is more on simulation data rather than experimental data, and more on materials rather than drug design. Nevertheless, contributions from other fields are warmly welcome!

How to cite. See the button "Cite this repository" on the right side-bar.

🧙‍♂️ Discover other best-of lists or create your own.

Active learning 9 projects
Community resources 39 projects
Datasets 55 projects
Data Structures 4 projects
Density functional theory (ML-DFT) 39 projects
Educational Resources 32 projects
Explainable Artificial intelligence (XAI) 4 projects
Electronic structure methods (ML-ESM) 6 projects
General Tools 24 projects
Generative Models 18 projects
Interatomic Potentials (ML-IAP) 78 projects
Language Models 25 projects
Materials Discovery 14 projects
Mathematical tools 14 projects
Molecular Dynamics 15 projects
Probabilistic ML 1 projects
Reinforcement Learning 2 projects
Representation Engineering 31 projects
Representation Learning 63 projects
Universal Potentials 19 projects
Unsupervised Learning 10 projects
Visualization 6 projects
Wavefunction methods (ML-WFT) 7 projects
Others 1 projects

Explanation

🥇🥈🥉 Combined project-quality score
⭐️ Star count from GitHub
🐣 New project (less than 6 months old)
💤 Inactive project (6 months no activity)
💀 Dead project (12 months no activity)
📈📉 Project is trending up or down
➕ Project was recently added
👨‍💻 Contributors count from GitHub
🔀 Fork count from GitHub
📋 Issue count from GitHub
⏱️ Last update timestamp on package manager
📥 Download count from package manager
📦 Number of dependent projects

Active learning

Projects that focus on enabling active learning, iterative learning schemes for atomistic ML.

DP-GEN (🥇25 · ⭐ 400) - The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field. LGPL-3.0 ML-IAP MD workflows

GitHub (👨‍💻 76 · 🔀 200 · 📥 2.1K · 📦 8 · 📋 370 - 3% open · ⏱️ 15.09.2026):
```
git clone https://github.com/deepmodeling/dpgen
```
PyPi (📥 510 / month · 📦 2 · ⏱️ 17.09.2026):
```
pip install dpgen
```
Conda (📥 330 · ⏱️ 25.03.2025):
```
conda install -c deepmodeling dpgen
```

FLARE (🥈19 · ⭐ 360) - An open-source Python package for creating fast and accurate interatomic potentials. MIT C++ ML-IAP

GitHub (👨‍💻 44 · 🔀 78 · 📥 10 · 📦 12 · 📋 240 - 14% open · ⏱️ 19.09.2026):
```
git clone https://github.com/mir-group/flare
```

Bgolearn (🥈17 · ⭐ 160) - [NPJ Com. Mat.] Offical implement of Bgolearn. MIT materials-discovery probabilistic

GitHub (👨‍💻 4 · 🔀 23 · 📥 92 · ⏱️ 30.08.2026):
```
git clone https://github.com/Bin-Cao/Bgolearn
```
PyPi (📥 330 / month · ⏱️ 28.08.2026):
```
pip install Bgolearn
```

DP-GEN2 (🥈17 · ⭐ 43) - 2nd generation of the Deep Potential GENerator. LGPL-3.0 ML-IAP MD workflows

GitHub (👨‍💻 21 · 🔀 36 · 📦 6 · 📋 66 - 48% open · ⏱️ 07.09.2026):
```
git clone https://github.com/deepmodeling/dpgen2
```

IPSuite (🥉16 · ⭐ 25 · 💤) - A Python toolkit for FAIR development and deployment of machine-learned interatomic potentials. EPL-2.0 ML-IAP MD workflows HTC FAIR

GitHub (👨‍💻 9 · 🔀 13 · 📦 14 · 📋 180 - 49% open · ⏱️ 13.03.2026):
```
git clone https://github.com/zincware/IPSuite
```
PyPi (📥 300 / month · 📦 5 · ⏱️ 20.11.2025):
```
pip install ipsuite
```

Show 4 hidden projects...

flare++ (🥉12 · ⭐ 39 · 💀) - A many-body extension of the FLARE code. MIT C++ ML-IAP
Finetuna (🥉9 · ⭐ 71 · 💀) - Active Learning for Machine Learning Potentials. MIT
ACEHAL (🥉5 · ⭐ 16 · 💀) - Hyperactive Learning (HAL) Python interface for building Atomic Cluster Expansion potentials. Unlicensed Julia
ALEBREW (🥉4 · ⭐ 21 · 💀) - Official repository for the paper Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic.. Custom ML-IAP MD

Community resources

Projects that collect atomistic ML resources or foster communication within community.

🔗 ACE / GRACE support - Support forum for the Atomic Cluster Expansion (ACE) and extensions.

🔗 AI for Science Map - Interactive mindmap of the AI4Science research field, including atomistic machine learning, including papers,..

🔗 ASE ecosystem - This is a list of software packages related to ASE or using ASE. md, ml-iap

🔗 Atomic Cluster Expansion - Atomic Cluster Expansion (ACE) community homepage.

🔗 CrystaLLM - Generate a crystal structure from a composition. language-models generative pretrained transformer

🔗 GAP-ML.org community homepage ML-IAP

🔗 matsci.org - A community forum for the discussion of anything materials science, with a focus on computational materials science..

🔗 Matter Modeling Stack Exchange - Machine Learning - Forum StackExchange, site Matter Modeling, ML-tagged questions.

MatBench Discovery (🥇22 · ⭐ 260) - An evaluation framework for machine learning models simulating high-throughput materials discovery. MIT datasets benchmarking model-repository

GitHub (👨‍💻 36 · 🔀 71 · 📥 29K · 📦 8 · 📋 78 - 3% open · ⏱️ 03.10.2026):
```
git clone https://github.com/janosh/matbench-discovery
```
PyPi (📥 1.9K / month · 📦 2 · ⏱️ 11.09.2024):
```
pip install matbench-discovery
```

Best-of Machine Learning with Python (🥇21 · ⭐ 24K · 💤) - A ranked list of awesome machine learning Python libraries. Updated weekly. CC-BY-4.0 general-ml Python

GitHub (👨‍💻 57 · 🔀 3.1K · 📋 70 - 50% open · ⏱️ 22.03.2026):
```
git clone https://github.com/ml-tooling/best-of-ml-python
```

OpenML (🥇21 · ⭐ 760) - Open Machine Learning. BSD-3 datasets

GitHub (👨‍💻 35 · 🔀 130 · 📋 1K - 37% open · ⏱️ 08.10.2026):
```
git clone https://github.com/openml/OpenML
```

Graph-based Deep Learning Literature (🥇18 · ⭐ 5.1K) - links to conference publications in graph-based deep learning. MIT general-ml rep-learn

GitHub (👨‍💻 12 · 🔀 770 · ⏱️ 28.09.2026):

git clone https://github.com/naganandy/graph-based-deep-learning-literature

ML-PEG (🥇18 · ⭐ 68) - ML Performance and Extrapolation Guide. GPL-3.0 benchmarking viz datasets structure-optimization MD transport-phenomena biomolecules long-range electrostatics

GitHub (👨‍💻 41 · 🔀 58 · 📥 60 · 📋 370 - 50% open · ⏱️ 08.10.2026):
```
git clone https://github.com/ddmms/ml-peg
```
PyPi (📥 140 / month · ⏱️ 03.10.2026):
```
pip install ml-peg
```

Garden (🥈16 · ⭐ 41 · 💤) - FAIR AI/ML Model Publishing Framework. MIT model-repository

GitHub (👨‍💻 14 · 🔀 5 · 📦 6 · 📋 380 - 3% open · ⏱️ 18.03.2026):
```
git clone https://github.com/Garden-AI/garden
```
PyPi (📥 760 / month · ⏱️ 18.03.2026):
```
pip install garden-ai
```

GT4SD - Generative Toolkit for Scientific Discovery (🥈15 · ⭐ 380) - Gradio apps of generative models in GT4SD. MIT generative pretrained drug-discovery model-repository

GitHub (👨‍💻 20 · 🔀 81 · 📋 120 - 1% open · ⏱️ 10.09.2026):
```
git clone https://github.com/GT4SD/gt4sd-core
```

AI for Science Resources (🥈13 · ⭐ 800) - List of resources for AI4Science research, including learning resources. GPL-3.0 license

GitHub (👨‍💻 37 · 🔀 96 · 📋 32 - 18% open · ⏱️ 01.10.2026):
```
git clone https://github.com/divelab/AIRS
```

GNoME Explorer (🥈12 · ⭐ 1.2K) - Graph Networks for Materials Exploration Database. Apache-2 datasets materials-discovery

GitHub (👨‍💻 3 · 🔀 200 · 📋 37 - 89% open · ⏱️ 29.04.2026):
```
git clone https://github.com/google-deepmind/materials_discovery
```

Neural-Network-Models-for-Chemistry (🥈12 · ⭐ 200) - A collection of Neural Network Models for chemistry. MIT rep-learn

GitHub (👨‍💻 3 · 🔀 22 · 📋 2 - 50% open · ⏱️ 09.04.2026):
```
git clone https://github.com/Eipgen/Neural-Network-Models-for-Chemistry
```

Awesome-Scientific-Language-Models (🥈10 · ⭐ 660) - A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery (EMNLP24). MIT language-models general-ml pretrained multimodal

GitHub (👨‍💻 9 · 🔀 37 · ⏱️ 16.09.2026):

git clone https://github.com/yuzhimanhua/Awesome-Scientific-Language-Models

Awesome Materials & Chemistry Datasets (🥉9 · ⭐ 390) - A curated list of the most useful datasets in materials science and chemistry for training machine learning and AI.. MIT datasets experimental-data literature-data proprietary

GitHub (👨‍💻 10 · 🔀 46 · 📋 15 - 26% open · ⏱️ 28.07.2026):
```
git clone https://github.com/blaiszik/awesome-matchem-datasets
```

optimade.science (🥉9 · ⭐ 10) - A sky-scanner Optimade browser-only GUI. MIT datasets

GitHub (👨‍💻 9 · 🔀 4 · 📋 26 - 26% open · ⏱️ 06.07.2026):
```
git clone https://github.com/tilde-lab/optimade.science
```

Awesome Neural Geometry (🥉8 · ⭐ 1.1K · 💤) - A curated collection of resources and research related to the geometry of representations in the brain, deep networks,.. Unlicensed educational rep-learn

GitHub (👨‍💻 16 · 🔀 72 · ⏱️ 24.02.2026):

git clone https://github.com/neurreps/awesome-neural-geometry

Awesome Neural SBI (🥉8 · ⭐ 170 · 💤) - Community-sourced list of papers and resources on neural simulation-based inference. MIT active-learning

GitHub (👨‍💻 7 · 🔀 8 · 📋 2 - 50% open · ⏱️ 28.01.2026):
```
git clone https://github.com/smsharma/awesome-neural-sbi
```

DeepModeling Projects (🥉8 · ⭐ 8) - DeepModeling projects. CC-BY-4.0

GitHub (👨‍💻 4 · 🔀 3 · ⏱️ 10.04.2026):

git clone https://github.com/deepmodeling/deepmodeling-projects

The Collection of Database and Dataset Resources in Materials Science (🥉7 · ⭐ 460) - A list of databases, datasets and books/handbooks where you can find materials properties for machine learning.. Unlicensed datasets

GitHub (👨‍💻 2 · 🔀 63 · ⏱️ 17.07.2026):

git clone https://github.com/sedaoturak/data-resources-for-materials-science

Awesome-Crystal-GNNs (🥉7 · ⭐ 120 · 💤) - This repository contains a collection of resources and papers on GNN Models on Crystal Solid State Materials. MIT

GitHub (👨‍💻 2 · 🔀 13 · ⏱️ 09.03.2026):

git clone https://github.com/kdmsit/Awesome-Crystal-GNNs

Charting ML Publications in Science (🥉6 · ⭐ 47 · 💤) - Literature analysis of ML applications in materials science, chemistry, physics. MIT literature-data general-ml

GitHub (👨‍💻 2 · ⏱️ 10.03.2026):

git clone https://github.com/blaiszik/ml_publication_charts

Show 12 hidden projects...

MatBench (🥇18 · ⭐ 220 · 💀) - Matbench: Benchmarks for materials science property prediction. MIT datasets benchmarking model-repository
Awesome Materials Informatics (🥈11 · ⭐ 530 · 💀) - Curated list of known efforts in materials informatics, i.e. in modern materials science. Custom
MoLFormers UI (🥉9 · ⭐ 420 · 💀) - A family of foundation models trained on chemicals. Apache-2 transformer language-models pretrained drug-discovery
Awesome-Graph-Generation (🥉8 · ⭐ 360 · 💀) - A curated list of up-to-date graph generation papers and resources. Unlicensed rep-learn
AI for Science paper collection (🥉8 · ⭐ 180 · 💀) - List the AI for Science papers accepted by top conferences. Apache-2
A Highly Opinionated List of Open-Source Materials Informatics Resources (🥉8 · ⭐ 160 · 💀) - A Highly Opinionated List of Open Source Materials Informatics Resources. MIT
MADICES Awesome Interoperability (🥉7 · ⭐ 1) - Linked data interoperability resources of the Machine-actionable data interoperability for the chemical sciences.. MIT datasets
LAM Crystal Philately competition 2024 (🥉5 · ⭐ 23 · 💀) - OpenLAM Challenge crystal structure prediction https://arxiv.org/abs/2501.16358. LGPL-2.1 single-paper datasets structure-prediction materials-discovery ML-IAP UIP
Geometric-GNNs (🥉4 · ⭐ 120 · 💀) - List of Geometric GNNs for 3D atomic systems. Unlicensed datasets educational rep-learn
Does this material exist? (🥉3 · ⭐ 18 · 💀) - Vote on whether you think predicted crystal structures could be synthesised. MIT for-fun materials-discovery
GitHub topic materials-informatics (🥉1) - GitHub topic materials-informatics. Unlicensed
MateriApps (🥉1) - A Portal Site of Materials Science Simulation. Unlicensed

Datasets

Datasets, databases and trained models for atomistic ML.

🔗 Alexandria Materials Database - A database of millions of theoretical crystal structures (3D, 2D and 1D) discovered by machine learning accelerated..

🔗 Catalysis Hub - A web-platform for sharing data and software for computational catalysis research!.

🔗 Citrination Datasets - AI-Powered Materials Data Platform. Open Citrination has been decommissioned.

🔗 crystals.ai - Curated datasets for reproducible AI in materials science.

🔗 DeepChem Models - DeepChem models on HuggingFace. model-repository pretrained language-models

🔗 Graphs of Materials Project 20190401 - The dataset used to train the MEGNet interatomic potential. ML-IAP

🔗 HME21 Dataset - High-temperature multi-element 2021 dataset for the PreFerred Potential (PFP).. UIP

🔗 JARVIS-Leaderboard ( ⭐ 75 · 💀) - A large scale benchmark of materials design methods: https://www.nature.com/articles/s41524-024-01259-w. model-repository benchmarking community-resource educational

🔗 Materials Project - Charge Densities - Materials Project has started offering charge density information available for download via their public API.

🔗 Materials Project Trajectory (MPtrj) Dataset - The dataset used to train the CHGNet universal potential. UIP

🔗 matterverse.ai - Database of yet-to-be-sythesized materials predicted using state-of-the-art machine learning algorithms.

🔗 MPF.2021.2.8 - The dataset used to train the M3GNet universal potential. UIP

🔗 NRELMatDB - Computational materials database with the specific focus on materials for renewable energy applications including, but..

🔗 QM9 Charge Densities and Energies - QM9 molecules calculated with VASP using Atomic Simulation Environment. ML-DFT

🔗 QM40 Dataset - A More Realistic QM Dataset for Machine Learning in Molecular Science https://doi.org/10.1038/s41597-024-04206-y. drug-discovery

🔗 QMugs dataset - Quantum Mechanical Properties of Drug-like Molecules https://doi.org/10.1038/s41597-022-01390-7. drug-discovery

🔗 Quantum-Machine.org Datasets - Collection of datasets, including QM7, QM9, etc. MD, DFT. Small organic molecules, mostly.

🔗 sGDML Datasets - MD17, MD22, DFT datasets.

🔗 MoleculeNet - A Benchmark for Molecular Machine Learning. benchmarking

🔗 ZINC15 - A free database of commercially-available compounds for virtual screening. ZINC contains over 230 million purchasable.. graph biomolecules

🔗 ZINC20 - A free database of commercially-available compounds for virtual screening. ZINC contains over 230 million purchasable.. graph biomolecules

FAIR Chemistry datasets (🥇31 · ⭐ 2.3K) - Datasets OC20, OC22, etc. Formerly known as Open Catalyst Project. MIT catalysis

GitHub (👨‍💻 74 · 🔀 510 · 📋 610 - 1% open · ⏱️ 08.10.2026):
```
git clone https://github.com/FAIR-Chem/fairchem
```
PyPi (📥 19K / month · 📦 90 · ⏱️ 24.09.2026):
```
pip install fairchem-core
```

Meta Open Materials 2024 (OMat24) Dataset (🥇30 · ⭐ 2.3K) - Contains over 100 million Density Functional Theory calculations focused on structural and compositional diversity. CC-BY-4.0

GitHub (👨‍💻 74 · 🔀 510 · 📋 610 - 1% open · ⏱️ 08.10.2026):
```
git clone https://github.com/FAIR-Chem/fairchem
```
PyPi (📥 19K / month · 📦 90 · ⏱️ 24.09.2026):
```
pip install fairchem-core
```

MPContribs (🥇24 · ⭐ 42) - Platform for materials scientists to contribute and disseminate their materials data through Materials Project. MIT

GitHub (👨‍💻 33 · 🔀 28 · 📦 61 · 📋 120 - 29% open · ⏱️ 06.10.2026):
```
git clone https://github.com/materialsproject/MPContribs
```
PyPi (📥 5.3K / month · 📦 7 · ⏱️ 09.02.2026):
```
pip install mpcontribs-client
```

OPTIMADE Python tools (🥇22 · ⭐ 92 · 📉) - Tools for implementing and consuming OPTIMADE APIs in Python. MIT

GitHub (👨‍💻 37 · 🔀 54 · 📋 480 - 18% open · ⏱️ 06.08.2026):
```
git clone https://github.com/Materials-Consortia/optimade-python-tools
```
PyPi (📥 14K / month · 📦 4 · ⏱️ 21.06.2026):
```
pip install optimade
```
Conda (📥 210K · ⏱️ 06.09.2026):
```
conda install -c conda-forge optimade
```

Open Databases Integration for Materials Design (OPTIMADE) (🥈15 · ⭐ 110) - Specification of a common REST API for access to materials databases. CC-BY-4.0

GitHub (👨‍💻 24 · 🔀 39 · 📋 260 - 29% open · ⏱️ 31.08.2026):
```
git clone https://github.com/Materials-Consortia/OPTIMADE
```

load-atoms (🥈15 · ⭐ 49 · 💤) - download and manipulate atomistic datasets. MIT data-structures

GitHub (👨‍💻 5 · 🔀 5 · 📦 8 · 📋 35 - 14% open · ⏱️ 25.11.2025):
```
git clone https://github.com/jla-gardner/load-atoms
```
PyPi (📥 710 / month · 📦 3 · ⏱️ 25.11.2025):
```
pip install load-atoms
```

QH9 (🥈13 · ⭐ 800) - A Quantum Hamiltonian Prediction Benchmark. CC-BY-NC-SA-4.0 ML-DFT

GitHub (👨‍💻 37 · 🔀 96 · 📋 32 - 18% open · ⏱️ 01.10.2026):
```
git clone https://github.com/divelab/AIRS
```

MatPES (🥈13 · ⭐ 61) - A foundational potential energy dataset for materials. BSD-3 UIP ML-IAP

GitHub (👨‍💻 3 · 🔀 5 · 📋 10 - 20% open · ⏱️ 01.07.2026):
```
git clone https://github.com/materialsvirtuallab/matpes
```
PyPi (📥 160 / month · 📦 2 · ⏱️ 10.03.2025):
```
pip install matpes
```

nablaDFT (🥈12 · ⭐ 240 · 💤) - nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset. MIT ML-DFT ML-WFT drug-discovery ML-IAP benchmarking

GitHub (👨‍💻 9 · 🔀 25 · 📋 28 - 10% open · ⏱️ 31.12.2025):
```
git clone https://github.com/AIRI-Institute/nablaDFT
```

MPDS API (🥈12 · ⭐ 27) - Tutorials, notebooks, issue tracker, and website on the MPDS API: the data retrieval interface for the Materials.. CC-BY-4.0 phase-transition

GitHub (👨‍💻 5 · 🔀 7 · 📋 36 - 22% open · ⏱️ 23.08.2026):
```
git clone https://github.com/mpds-io/mpds-api
```
PyPi (📥 310 / month · ⏱️ 14.09.2020):
```
pip install mpds_client
```

SPICE (🥈11 · ⭐ 200 · 💤) - A collection of QM data for training potential functions. MIT ML-IAP MD

GitHub (👨‍💻 1 · 🔀 11 · 📥 410 · 📋 76 - 27% open · ⏱️ 25.02.2026):
```
git clone https://github.com/openmm/spice-dataset
```

OpenKIM (🥈11 · ⭐ 40 · 💤) - The Open Knowledgebase of Interatomic Models (OpenKIM) aims to be an online resource for standardized testing, long-.. LGPL-2.1 model-repository knowledge-base pretrained

GitHub (👨‍💻 27 · 🔀 20 · 📋 37 - 40% open · ⏱️ 06.03.2026):
```
git clone https://github.com/openkim/kim-api
```

OBELiX (🥉9 · ⭐ 62 · 💤) - A Curated Dataset of Crystal Structures and Experimentally Measured Ionic Conductivities for Lithium Solid-State.. CC-BY-4.0 experimental-data transport-phenomena

GitHub (👨‍💻 6 · 🔀 9 · 📋 2 - 50% open · ⏱️ 27.11.2025):
```
git clone https://github.com/NRC-Mila/OBELiX
```
PyPi (📥 86 / month · ⏱️ 16.05.2025):
```
pip install obelix-data
```

polyVERSE (🥉9 · ⭐ 47) - polyVERSE is a comprehensive repository of informatics-ready datasets curated by the Ramprasad Group. Custom soft-matter

GitHub (👨‍💻 11 · 🔀 8 · ⏱️ 23.08.2026):

git clone https://github.com/Ramprasad-Group/polyVERSE

AIS Square (🥉9 · ⭐ 15) - A collaborative and open-source platform for sharing AI for Science datasets, models, and workflows. Home of the.. LGPL-3.0 community-resource model-repository

GitHub (👨‍💻 8 · 🔀 10 · 📋 6 - 83% open · ⏱️ 08.10.2026):
```
git clone https://github.com/deepmodeling/AIS-Square
```

The Perovskite Database Project (🥉5 · ⭐ 75 · 💤) - Perovskite Database Project aims at making all perovskite device data, both past and future, available in a form.. Unlicensed community-resource

GitHub (👨‍💻 2 · 🔀 26 · ⏱️ 20.03.2026):

git clone https://github.com/Jesperkemist/perovskitedatabase

Visual Graph Datasets (🥉5 · ⭐ 5 · 💤) - Datasets for the training of graph neural networks (GNNs) and subsequent visualization of attributional explanations.. MIT XAI rep-learn

GitHub (👨‍💻 2 · 🔀 3 · ⏱️ 24.03.2026):

git clone https://github.com/aimat-lab/visual_graph_datasets

Show 17 hidden projects...

ATOM3D (🥈19 · ⭐ 320 · 💀) - ATOM3D: tasks on molecules in three dimensions. MIT biomolecules benchmarking
OpenQDC (🥈14 · ⭐ 68 · 💀) - Repository of Quantum Datasets Publicly Available. CC-BY-4.0
MoleculeNet Leaderboard (🥉9 · ⭐ 110 · 💀) - MIT benchmarking
Materials Data Facility (MDF) (🥉9 · ⭐ 10 · 💀) - A simple way to publish, discover, and access materials datasets. Publication of very large datasets supported (e.g.,.. Apache-2
2DMD dataset (🥉9 · ⭐ 8 · 💀) - Code for Kazeev, N., Al-Maeeni, A.R., Romanov, I. et al. Sparse representation for machine learning the properties of.. Apache-2 material-defect
ANI-1 Dataset (🥉8 · ⭐ 110 · 💀) - A data set of 20 million calculated off-equilibrium conformations for organic molecules. MIT
GEOM (🥉7 · ⭐ 260 · 💀) - GEOM: Energy-annotated molecular conformations. Unlicensed drug-discovery
SciGlass (🥉7 · ⭐ 17 · 💀) - The database contains a vast set of data on the properties of glass materials. MIT
ANI-1x Datasets (🥉6 · ⭐ 71 · 💀) - The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for organic molecules. MIT
COMP6 Benchmark dataset (🥉6 · ⭐ 42 · 💀) - COMP6 Benchmark dataset for ML potentials. MIT
GDB-9-Ex9 and ORNL_AISD-Ex (🥉5 · ⭐ 11 · 💀) - Distributed computing workflow for generation and analysis of large scale molecular datasets obtained running multi-.. Unlicensed
OPTIMADE providers dashboard (🥉5 · ⭐ 2 · 💀) - A dashboard of known providers. Unlicensed
3DSC Database (🥉4 · ⭐ 30 · 💀) - Repo for the paper publishing the superconductor database with 3D crystal structures. Custom superconductors materials-discovery
paper-data-redundancy (🥉4 · ⭐ 11 · 💀) - Repo for the paper Exploiting redundancy in large materials datasets for efficient machine learning with less data. BSD-3 small-data single-paper
linear-regression-benchmarks (🥉4 · ⭐ 1 · 💀) - Data sets used for linear regression benchmarks. MIT benchmarking single-paper
nep-data (🥉3 · ⭐ 21 · 💀) - Data related to the NEP machine-learned potential of GPUMD. Unlicensed ML-IAP MD transport-phenomena
tmQM_wB97MV Dataset (🥉1 · ⭐ 12 · 💀) - Code for Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV.. Unlicensed catalysis rep-learn

Data Structures

Projects that focus on providing data structures used in atomistic machine learning.

dpdata (🥇28 · ⭐ 250) - A Python package for manipulating atomistic data of software in computational science. LGPL-3.0

GitHub (👨‍💻 72 · 🔀 160 · 📦 160 · 📋 160 - 7% open · ⏱️ 12.09.2026):
```
git clone https://github.com/deepmodeling/dpdata
```
PyPi (📥 15K / month · 📦 47 · ⏱️ 19.08.2026):
```
pip install dpdata
```
Conda (📥 500 · ⏱️ 25.03.2025):
```
conda install -c deepmodeling dpdata
```

Metatensor (🥈23 · ⭐ 110 · 📉) - Self-describing sparse tensor data format for atomistic machine learning and beyond. BSD-3 ML-IAP MD Rust C-lang C++ Python

GitHub (👨‍💻 37 · 🔀 28 · 📥 58K · 📦 16 · 📋 270 - 20% open · ⏱️ 06.10.2026):
```
git clone https://github.com/metatensor/metatensor
```
PyPi (📥 1.2K / month · ⏱️ 26.01.2024):
```
pip install metatensor
```

mp-pyrho (🥉19 · ⭐ 43) - Tools for re-griding volumetric quantum chemistry data for machine-learning purposes. Custom ML-DFT

GitHub (👨‍💻 10 · 🔀 10 · 📦 38 · 📋 10 - 70% open · ⏱️ 11.05.2026):
```
git clone https://github.com/materialsproject/pyrho
```
PyPi (📥 74K / month · 📦 5 · ⏱️ 13.10.2025):
```
pip install mp-pyrho
```

dlpack (🥉16 · ⭐ 1.3K) - common in-memory tensor structure. Apache-2 C++

GitHub (👨‍💻 36 · 🔀 170 · 📋 90 - 28% open · ⏱️ 11.08.2026):
```
git clone https://github.com/dmlc/dlpack
```

Density functional theory (ML-DFT)

Projects and models that focus on quantities of DFT, such as density functional approximations (ML-DFA), the charge density, density of states, the Hamiltonian, etc.

🔗 IKS-PIML - Code and generated data for the paper Inverting the Kohn-Sham equations with physics-informed machine learning.. neural-operator pinn datasets single-paper

🔗 M-OFDFT - Overcoming the Barrier of Orbital-Free Density Functional Theory in Molecular Systems Using Deep Learning.. transformer single-paper

JAX-DFT (🥇26 · ⭐ 39K) - This library provides basic building blocks that can construct DFT calculations as a differentiable program. Apache-2

GitHub (👨‍💻 890 · 🔀 8.4K · 📋 2.3K - 84% open · ⏱️ 08.10.2026):
```
git clone https://github.com/google-research/google-research
```

HamGNN (🥇16 · ⭐ 220) - An E(3) equivariant Graph Neural Network for predicting electronic Hamiltonian matrix. GPL-3.0 rep-learn magnetism C-lang

GitHub (👨‍💻 9 · 🔀 48 · 📋 89 - 82% open · ⏱️ 18.09.2026):
```
git clone https://github.com/QuantumLab-ZY/HamGNN
```

SALTED (🥈15 · ⭐ 50) - Symmetry-Adapted Learning of Three-dimensional Electron Densities (and their electrostatic response). GPL-3.0

GitHub (👨‍💻 30 · 🔀 10 · 📋 17 - 11% open · ⏱️ 30.09.2026):
```
git clone https://github.com/andreagrisafi/SALTED
```

CiderPress (🥈15 · ⭐ 27) - A high-performance software package for training and evaluating machine-learned XC functionals using the CIDER.. GPL-3.0 ml-functional C-lang

GitHub (👨‍💻 3 · 🔀 4 · ⏱️ 27.08.2026):
```
git clone https://github.com/mir-group/CiderPress
```
PyPi (📥 68 / month · ⏱️ 27.08.2026):
```
pip install ciderpress
```

QHNet (🥈13 · ⭐ 800) - Artificial Intelligence Research for Science (AIRS). GPL-3.0 rep-learn

GitHub (👨‍💻 37 · 🔀 96 · 📋 32 - 18% open · ⏱️ 01.10.2026):
```
git clone https://github.com/divelab/AIRS
```

Q-stack (🥈12 · ⭐ 20) - Stack of codes for dedicated pre- and post-processing tasks for Quantum Machine Learning (QML). MIT excited-states general-tool

GitHub (👨‍💻 8 · 🔀 7 · 📋 57 - 15% open · ⏱️ 03.08.2026):
```
git clone https://github.com/lcmd-epfl/Q-stack
```

MLDensity (🥈10 · ⭐ 9 · 📈) - Linear Jacobi-Legendre expansion of the charge density for machine learning-accelerated electronic structure.. LGPL-3.0

GitHub (👨‍💻 4 · ⏱️ 05.10.2026):

git clone https://github.com/StefanoSanvitoGroup/MLdensity

dftio (🥉8 · ⭐ 16 · 💤) - dftio is to assist machine learning communities to transcript DFT output into a format that is easy to read or used by.. LGPL-3.0 data-structures workflows

GitHub (👨‍💻 5 · 🔀 14 · 📋 26 - 84% open · ⏱️ 18.12.2025):
```
git clone https://github.com/deepmodeling/dftio
```

DeepH-E3 (🥉7 · ⭐ 120 · 💤) - General framework for E(3)-equivariant neural network representation of density functional theory Hamiltonian. MIT magnetism

GitHub (👨‍💻 2 · 🔀 29 · 📋 40 - 67% open · ⏱️ 27.01.2026):
```
git clone https://github.com/Xiaoxun-Gong/DeepH-E3
```

Show 28 hidden projects...

DM21 (🥇19 · ⭐ 15K · 💀) - This package provides a PySCF interface to the DM21 (DeepMind 21) family of exchange-correlation functionals described.. Apache-2
MALA (🥇16 · ⭐ 100 · 💀) - Materials Learning Algorithms. A framework for machine learning materials properties from first-principles data. BSD-3
DeepH-pack (🥈12 · ⭐ 340 · 💀) - Deep neural networks for density functional theory Hamiltonian. LGPL-3.0 Julia
Grad DFT (🥈10 · ⭐ 110 · 💀) - GradDFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation.. Apache-2
NeuralXC (🥈10 · ⭐ 39 · 💀) - Implementation of a machine learned density functional. BSD-3
DeePKS-kit (🥈9 · ⭐ 120 · 💀) - a package for developing machine learning-based chemically accurate energy and density functional models. LGPL-3.0 ml-functional
PROPhet (🥈9 · ⭐ 66 · 💀) - PROPhet is a code to integrate machine learning techniques with first-principles quantum chemistry approaches. GPL-3.0 ML-IAP MD single-paper C++
ACEhamiltonians (🥈9 · ⭐ 17 · 💀) - Provides tools for constructing, fitting, and predicting self-consistent Hamiltonian and overlap matrices in solid-.. MIT Julia
ChargE3Net (🥉8 · ⭐ 76 · 💀) - [npj Comp. Mat.] Higher-order equivariant neural networks for charge density prediction in materials. MIT rep-learn
Libnxc (🥉8 · ⭐ 21 · 💀) - A library for using machine-learned exchange-correlation functionals for density-functional theory. MPL-2.0 C++ Fortran
Mat2Spec (🥉7 · ⭐ 32 · 💀) - Density of States Prediction for Materials Discovery via Contrastive Learning from Probabilistic Embeddings. MIT spectroscopy
DeepDFT (🥉6 · ⭐ 90 · 💀) - Official implementation of DeepDFT model. MIT
scdp (scalable charge density prediction) (🥉6 · ⭐ 42 · 💀) - [NeurIPS 2024] source code for A Recipe for Charge Density Prediction. MIT rep-learn single-paper
charge-density-models (🥉6 · ⭐ 16 · 💀) - Tools to build charge density models using fairchem. MIT rep-learn
KSR-DFT (🥉6 · ⭐ 4 · 💀) - Kohn-Sham regularizer for machine-learned DFT functionals. Apache-2
xDeepH (🥉5 · ⭐ 41 · 💀) - Extended DeepH (xDeepH) method for magnetic materials. LGPL-3.0 magnetism Julia
InfGCN for Electron Density Estimation (🥉5 · ⭐ 17 · 💀) - Official implementation of the NeurIPS 23 spotlight paper of InfGCN. MIT rep-learn neural-operator
rho_learn (🥉5 · ⭐ 4 · 💀) - A proof-of-concept workflow for torch-based electron density learning. MIT ML-DFT rep-eng
ML-DFT (🥉4 · ⭐ 29 · 💀) - A package for density functional approximation using machine learning. MIT
DeepCDP (🥉4 · ⭐ 6 · 💀) - DeepCDP: Deep learning Charge Density Prediction. Unlicensed
CSNN (🥉4 · ⭐ 3 · 💀) - Primary codebase of CSNN - Concentric Spherical Neural Network for 3D Representation Learning. BSD-3
rholearn (🥉4 · ⭐ 3 · 💀) - Learning and predicting electronic densities decomposed on a basis and global electronic densities of states at DFT.. MIT ML-DFT rep-eng density-of-states
MALADA (🥉4 · ⭐ 1 · 💀) - MALA Data Acquisition: Helpful tools to build data for MALA. BSD-3
gprep (🥉4 · 💀) - Fitting DFTB repulsive potentials with GPR. MIT single-paper
ofdft_nflows (🥉3 · ⭐ 12 · 💀) - Nomalizing flows for orbita-free DFT. Unlicensed generative
APET (🥉3 · ⭐ 6 · 💀) - Atomic Positional Embedding-based Transformer. GPL-3.0 density-of-states transformer
A3MD (🥉2 · ⭐ 8 · 💀) - MPNN-like + Analytic Density Model = Accurate electron densities. Unlicensed rep-learn single-paper
kdft (🥉1 · ⭐ 1 · 💀) - The Kernel Density Functional (KDF) code allows generating ML based DFT functionals. Unlicensed

Educational Resources

Tutorials, guides, cookbooks, recipes, etc.

🔗 AI for Science 101 community-resource rep-learn

🔗 AL4MS 2023 workshop tutorials active-learning

🔗 Quantum Chemistry in the Age of Machine Learning - Book, 2022.

COSMO Software Cookbook (🥇14 · ⭐ 56) - A collection of simulation recipes for the atomic-scale modeling of materials and molecules. BSD-3

GitHub (👨‍💻 23 · 🔀 12 · 📋 35 - 31% open · ⏱️ 05.10.2026):
```
git clone https://github.com/lab-cosmo/software-cookbook
```

Geometric GNN Dojo (🥇12 · ⭐ 520 · 💤) - New to geometric GNNs: try our practical notebook, prepared for MPhil students at the University of Cambridge. MIT rep-learn

GitHub (👨‍💻 4 · 🔀 55 · 📋 9 - 22% open · ⏱️ 09.10.2025):
```
git clone https://github.com/chaitjo/geometric-gnn-dojo
```

Deep Learning for Molecules and Materials Book (🥈11 · ⭐ 750 · 💤) - Deep learning for molecules and materials book. Custom

GitHub (👨‍💻 19 · 🔀 130 · 📋 180 - 17% open · ⏱️ 20.02.2026):
```
git clone https://github.com/whitead/dmol-book
```

AI4Chemistry course (🥈11 · ⭐ 290) - EPFL AI for chemistry course, Spring 2023. https://schwallergroup.github.io/ai4chem_course. MIT chemistry

GitHub (👨‍💻 10 · 🔀 63 · 📋 6 - 50% open · ⏱️ 03.04.2026):
```
git clone https://github.com/schwallergroup/ai4chem_course
```

DSECOP (🥈9 · ⭐ 56) - This repository contains data science educational materials developed by DSECOP Fellows. CCO-1.0

GitHub (👨‍💻 15 · 🔀 26 · 📋 8 - 12% open · ⏱️ 25.08.2026):
```
git clone https://github.com/GDS-Education-Community-of-Practice/DSECOP
```

iam-notebooks (🥈9 · ⭐ 38) - Jupyter notebooks for the lectures of the Introduction to Atomistic Modeling. Apache-2

GitHub (👨‍💻 7 · 🔀 6 · ⏱️ 22.05.2026):

git clone https://github.com/ceriottm/iam-notebooks

MLforMaterials (🥈8 · ⭐ 170 · 💤) - Online resource for a practical course in machine learning for materials research at Imperial College London.. MIT community-resource general-ml rep-eng materials-discovery

GitHub (👨‍💻 2 · 🔀 20 · 📋 4 - 25% open · ⏱️ 07.02.2026):
```
git clone https://github.com/aronwalsh/MLforMaterials
```

MACE-tutorials (🥉6 · ⭐ 77 · 💤) - Another set of tutorials for the MACE interatomic potential by one of the authors. MIT ML-IAP rep-learn MD

GitHub (👨‍💻 2 · 🔀 18 · ⏱️ 22.01.2026):

git clone https://github.com/ilyes319/mace-tutorials

DeepModeling Tutorials (🥉6 · ⭐ 18 · 💤) - Tutorials for DeepModeling projects. Unlicensed

GitHub (👨‍💻 12 · 🔀 24 · 📋 4 - 25% open · ⏱️ 11.03.2026):
```
git clone https://github.com/deepmodeling/tutorials
```

Show 20 hidden projects...

DeepLearningLifeSciences (🥇12 · ⭐ 420 · 💀) - Example code from the book Deep Learning for the Life Sciences. MIT
Introduction to AI-driven Science on Supercomputers: A Student Training Series (🥈11 · ⭐ 240 · 💤) - Unlicensed general-ml rep-learn language-models
jarvis-tools-notebooks (🥈9 · ⭐ 97 · 💀) - This repository is no longer maintained. For the latest updates and continued development, please visit:.. NIST
OPTIMADE Tutorial Exercises (🥈9 · ⭐ 17 · 💀) - Tutorial exercises for the OPTIMADE API. MIT datasets
RDKit Tutorials (🥈8 · ⭐ 320 · 💀) - Tutorials to learn how to work with the RDKit. Custom
BestPractices (🥈8 · ⭐ 210 · 💀) - Things that you should (and should not) do in your Materials Informatics research. MIT
MAChINE (🥉7 · ⭐ 1 · 💀) - Client-Server Web App to introduce usage of ML in materials science to beginners. MIT
Applied AI for Materials (🥉6 · ⭐ 87 · 💀) - Course materials for Applied AI for Materials Science and Engineering. Unlicensed
Machine Learning for Materials Hard and Soft (🥉6 · ⭐ 40 · 💀) - ESI-DCAFM-TACO-VDSP Summer School on Machine Learning for Materials Hard and Soft. Unlicensed
ML for catalysis tutorials (🥉6 · ⭐ 12 · 💀) - A jupyter book repo for tutorial on how to use OCP ML models for catalysis. MIT
Data Handling, DoE and Statistical Analysis for Material Chemists (🥉6 · ⭐ 4 · 💀) - Notebooks for workshops of DoE course, hosted by the Computational Materials Chemistry group at Uppsala University. GPL-3.0
AI4Science101 (🥉5 · ⭐ 100 · 💀) - AI for Science. Unlicensed
ML-in-chemistry-101 (🥉4 · ⭐ 91 · 💀) - The course materials for Machine Learning in Chemistry 101. Unlicensed
DSM-CORE (🥉4 · ⭐ 17 · 💀) - Data Science for Materials - Collection of Open Educational Resources. Unlicensed
chemrev-gpr (🥉4 · ⭐ 11 · 💀) - Notebooks accompanying the paper on GPR in materials and molecules in Chemical Reviews 2020. Unlicensed
AI4ChemMat Hands-On Series (🥉4 · ⭐ 1 · 💀) - Hands-On Series organized by Chemistry and Materials working group at Argonne Nat Lab. MPL-2.0
PiNN Lab (🥉3 · ⭐ 3 · 💀) - Material for running a lab session on atomic neural networks. GPL-3.0
MLDensity_tutorial (🥉2 · ⭐ 12 · 💀) - Tutorial files to work with ML for the charge density in molecules and solids. Unlicensed
LAMMPS-style pair potentials with GAP (🥉2 · ⭐ 4 · 💀) - A tutorial on how to create LAMMPS-style pair potentials and use them in combination with GAP potentials to run MD.. Unlicensed ML-IAP MD rep-eng
MALA Tutorial (🥉2 · ⭐ 2 · 💀) - A full MALA hands-on tutorial. Unlicensed

Explainable Artificial intelligence (XAI)

Projects that focus on explainability and model interpretability in atomistic ML.

MEGAN: Multi Explanation Graph Attention Student (🥈8 · ⭐ 12) - Minimal implementation of graph attention student model architecture. MIT rep-learn

GitHub (👨‍💻 2 · 🔀 2 · 📋 3 - 33% open · ⏱️ 15.08.2026):
```
git clone https://github.com/aimat-lab/graph_attention_student
```

Show 3 hidden projects...

exmol (🥇19 · ⭐ 360 · 💀) - Explainer for black box models that predict molecule properties. MIT
Linear vs blackbox (🥉3 · ⭐ 2 · 💀) - Code and data related to the publication: Interpretable models for extrapolation in scientific machine learning. MIT XAI single-paper rep-eng
XElemNet (🥉2 · 💀) - Using explainable artificial intelligence (XAI) techniques to analyze ElemNet... Unlicensed rep-eng single-paper

Electronic structure methods (ML-ESM)

Projects and models that focus on quantities of electronic structure methods, which do not fit into either of the categories ML-WFT or ML-DFT.

DeePTB (🥇14 · ⭐ 120) - DeePTB: A deep learning package for tight-binding Hamiltonian with ab initio accuracy. LGPL-3.0 ML-DFT

GitHub (👨‍💻 15 · 🔀 34 · 📦 4 · 📋 80 - 47% open · ⏱️ 15.07.2026):
```
git clone https://github.com/deepmodeling/DeePTB
```
PyPi (📥 220 / month · 📦 2 · ⏱️ 20.06.2026):
```
pip install dptb
```

Show 5 hidden projects...

QDF for molecule (🥈8 · ⭐ 230 · 💀) - Quantum deep field: data-driven wave function, electron density generation, and energy prediction and extrapolation.. MIT
QMLearn (🥈5 · ⭐ 12 · 💀) - Quantum Machine Learning by learning one-body reduced density matrices in the AO basis... MIT
q-pac (🥈5 · ⭐ 6 · 💀) - Kernel charge equilibration method. MIT electrostatics
halex (🥈5 · ⭐ 5 · 💀) - Hamiltonian Learning for Excited States https://doi.org/10.48550/arXiv.2311.00844. Unlicensed excited-states
e3psi (🥉4 · ⭐ 7 · 💀) - Equivariant machine learning library for learning from electronic structures. LGPL-3.0

General Tools

General tools for atomistic machine learning.

RDKit (🥇38 · ⭐ 3.6K · 📉) - BSD-3 C++ cheminformatics

GitHub (👨‍💻 290 · 🔀 1.1K · 📦 310 · 📋 3.8K - 2% open · ⏱️ 03.10.2026):
```
git clone https://github.com/rdkit/rdkit
```
PyPi (📥 4.7M / month · 📦 2.2K · ⏱️ 03.09.2026):
```
pip install rdkit
```
Conda (📥 2.6M · ⏱️ 25.03.2025):
```
conda install -c rdkit rdkit
```

DeepChem (🥇33 · ⭐ 7K · 📉) - Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology. MIT

GitHub (👨‍💻 260 · 🔀 2.3K · 📦 670 · 📋 2.5K - 47% open · ⏱️ 20.08.2026):
```
git clone https://github.com/deepchem/deepchem
```
PyPi (📥 21K / month · 📦 32 · ⏱️ 21.08.2026):
```
pip install deepchem
```
Conda (📥 130K · ⏱️ 22.04.2025):
```
conda install -c conda-forge deepchem
```
Docker Hub (📥 12K · ⭐ 5 · ⏱️ 15.07.2025):
```
docker pull deepchemio/deepchem
```

Matminer (🥇27 · ⭐ 620) - Data mining for materials science. Custom

GitHub (👨‍💻 58 · 🔀 220 · 📦 500 · 📋 240 - 14% open · ⏱️ 30.06.2026):
```
git clone https://github.com/hackingmaterials/matminer
```
PyPi (📥 40K / month · 📦 89 · ⏱️ 14.04.2026):
```
pip install matminer
```
Conda (📥 130K · ⏱️ 06.09.2026):
```
conda install -c conda-forge matminer
```

QUIP (🥈25 · ⭐ 410) - libAtoms/QUIP molecular dynamics framework: https://libatoms.github.io. GPL-2.0 MD ML-IAP rep-eng Fortran

GitHub (👨‍💻 87 · 🔀 130 · 📥 1K · 📦 46 · 📋 500 - 23% open · ⏱️ 12.05.2026):
```
git clone https://github.com/libAtoms/QUIP
```
PyPi (📥 1.5K / month · 📦 9 · ⏱️ 30.04.2026):
```
pip install quippy-ase
```
Docker Hub (📥 11K · ⭐ 4 · ⏱️ 24.04.2023):
```
docker pull libatomsquip/quip
```

Molfeat (🥈24 · ⭐ 230) - molfeat - the hub for all your molecular featurizers. Apache-2 cheminformatics rep-eng rep-learn generative language-models pretrained

GitHub (👨‍💻 22 · 🔀 31 · 📦 79 · 📋 59 - 15% open · ⏱️ 09.09.2026):
```
git clone https://github.com/datamol-io/molfeat
```
PyPi (📥 4.4K / month · 📦 20 · ⏱️ 09.09.2026):
```
pip install molfeat
```
Conda (📥 52K · ⏱️ 28.09.2026):
```
conda install -c conda-forge molfeat
```

MAML (🥈21 · ⭐ 470) - Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc. BSD-3

GitHub (👨‍💻 39 · 🔀 96 · 📦 17 · 📋 76 - 14% open · ⏱️ 27.07.2026):
```
git clone https://github.com/materialsvirtuallab/maml
```
PyPi (📥 490 / month · 📦 3 · ⏱️ 02.04.2025):
```
pip install maml
```

Scikit-Matter (🥈20 · ⭐ 98) - A collection of scikit-learn compatible utilities that implement methods born out of the materials science and.. BSD-3 scikit-learn

GitHub (👨‍💻 19 · 🔀 27 · 📥 29 · 📋 84 - 23% open · ⏱️ 27.08.2026):
```
git clone https://github.com/scikit-learn-contrib/scikit-matter
```
PyPi (📥 11K / month · 📦 7 · ⏱️ 27.08.2026):
```
pip install skmatter
```
Conda (📥 9.9K · ⏱️ 29.08.2026):
```
conda install -c conda-forge skmatter
```

MLatom (🥈18 · ⭐ 170) - AI-enhanced computational chemistry. MIT UIP ML-IAP MD ML-DFT ML-ESM transfer-learning active-learning spectroscopy structure-optimization

GitHub (👨‍💻 8 · 🔀 26 · 📋 10 - 50% open · ⏱️ 12.09.2026):
```
git clone https://github.com/dralgroup/mlatom
```
PyPi (📥 890 / month · 📦 3 · ⏱️ 12.09.2026):
```
pip install mlatom
```

MAST-ML (🥉14 · ⭐ 130 · 💤) - MAterials Simulation Toolkit for Machine Learning (MAST-ML). MIT

GitHub (👨‍💻 19 · 🔀 61 · 📥 180 · 📋 220 - 14% open · ⏱️ 10.10.2025):
```
git clone https://github.com/uw-cmg/MAST-ML
```

Artificial Intelligence for Science (AIRS) (🥉13 · ⭐ 800) - Artificial Intelligence Research for Science (AIRS). GPL-3.0 license rep-learn generative ML-IAP MD ML-DFT ML-WFT biomolecules

GitHub (👨‍💻 37 · 🔀 96 · 📋 32 - 18% open · ⏱️ 01.10.2026):
```
git clone https://github.com/divelab/AIRS
```

Show 14 hidden projects...

JARVIS-Tools (🥈23 · ⭐ 400 · 💀) - About JARVIS-Tools: an open-source software package for data-driven atomistic materials design. Publications:.. Custom
AtomAI (🥈18 · ⭐ 230 · 💀) - Deep and Machine Learning for Microscopy. MIT computer-vision USL experimental-data
Automatminer (🥉16 · ⭐ 180 · 💀) - An automatic engine for predicting materials properties. Custom autoML
XenonPy (🥉16 · ⭐ 160 · 💀) - XenonPy is a Python Software for Materials Informatics. BSD-3
QML (🥉15 · ⭐ 210 · 💀) - QML: Quantum Machine Learning. MIT
AMPtorch (🥉11 · ⭐ 62 · 💀) - AMPtorch: Atomistic Machine Learning Package (AMP) - PyTorch. GPL-3.0
OpenChem (🥉10 · ⭐ 750 · 💀) - OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research. MIT
JAXChem (🥉7 · ⭐ 85 · 💀) - JAXChem is a JAX-based deep learning library for complex and versatile chemical modeling. MIT
uncertainty_benchmarking (🥉7 · ⭐ 44 · 💀) - Various code/notebooks to benchmark different ways we could estimate uncertainty in ML predictions. Unlicensed benchmarking probabilistic
torchchem (🥉7 · ⭐ 38 · 💀) - An experimental repo for experimenting with PyTorch models. MIT
Equisolve (🥉6 · ⭐ 5 · 💀) - A ML toolkit package utilizing the metatensor data format to build models for the prediction of equivariant properties.. BSD-3 ML-IAP
quantum-structure-ml (🥉3 · ⭐ 3 · 💀) - Multi-class classification model for predicting the magnetic order of magnetic structures and a binary classification.. Unlicensed magnetism benchmarking
ACEatoms (🥉3 · ⭐ 2 · 💀) - Generic code for modelling atomic properties using ACE. Custom Julia
Magpie (🥉3) - Materials Agnostic Platform for Informatics and Exploration (Magpie). MIT Java

Generative Models

Projects that implement generative models for atomistic ML.

GT4SD (🥇17 · ⭐ 380) - GT4SD, an open-source library to accelerate hypothesis generation in the scientific discovery process. MIT pretrained drug-discovery rep-learn

GitHub (👨‍💻 20 · 🔀 81 · 📋 120 - 1% open · ⏱️ 10.09.2026):
```
git clone https://github.com/GT4SD/gt4sd-core
```
PyPi (📥 170 / month · ⏱️ 31.07.2026):
```
pip install gt4sd
```

PMTransformer (🥇15 · ⭐ 130) - Universal Transfer Learning in Porous Materials, including MOFs. MIT transfer-learning pretrained transformer

GitHub (👨‍💻 2 · 🔀 22 · 📦 8 · 📋 48 - 4% open · ⏱️ 23.05.2026):
```
git clone https://github.com/hspark1212/MOFTransformer
```
PyPi (📥 200 / month · 📦 1 · ⏱️ 20.06.2024):
```
pip install moftransformer
```

SiMGen (🥈13 · ⭐ 31) - Zero Shot Molecular Generation via Similarity Kernels. MIT viz

GitHub (👨‍💻 4 · 🔀 5 · 📦 2 · 📋 5 - 20% open · ⏱️ 30.08.2026):
```
git clone https://github.com/RokasEl/simgen
```
PyPi (📥 25 / month · ⏱️ 30.08.2026):
```
pip install simgen
```

SLICES and MatterGPT (🥈12 · ⭐ 150 · 💤) - SLICES: An Invertible, Invariant, and String-based Crystal Representation [2023, Nature Communications] MatterGPT,.. LGPL-2.1 rep-eng language-models transformer materials-discovery structure-prediction

GitHub (👨‍💻 2 · 🔀 56 · 📦 7 · 📋 17 - 23% open · ⏱️ 03.03.2026):
```
git clone https://github.com/xiaohang007/SLICES
```
PyPi (📥 180 / month · 📦 1 · ⏱️ 14.10.2025):
```
pip install slices
```
Docker Hub (📥 1.1K · ⭐ 1 · ⏱️ 14.10.2025):
```
docker pull xiaohang07/slices
```

SchNetPack G-SchNet (🥈11 · ⭐ 65 · 💤) - G-SchNet extension for SchNetPack. MIT

GitHub (👨‍💻 3 · 🔀 11 · ⏱️ 13.11.2025):

git clone https://github.com/atomistic-machine-learning/schnetpack-gschnet

Matcha (🥉6 · ⭐ 36) - Multi-stage Riemannian flow matching for physically valid molecular docking, with GNINA scoring, PoseBusters.. Unlicensed drug-discovery cheminformatics rep-learn benchmarking

GitHub (👨‍💻 3 · 🔀 4 · 📋 4 - 50% open · ⏱️ 22.09.2026):
```
git clone https://github.com/LigandPro/Matcha
```

Show 12 hidden projects...

MoLeR (🥇15 · ⭐ 330 · 💀) - Implementation of MoLeR: a generative model of molecular graphs which supports scaffold-constrained generation. MIT
synspace (🥈14 · ⭐ 49 · 💀) - Synthesis generative model. MIT
EDM (🥉9 · ⭐ 580 · 💀) - E(3) Equivariant Diffusion Model for Molecule Generation in 3D. MIT
G-SchNet (🥉8 · ⭐ 150 · 💀) - G-SchNet - a generative model for 3d molecular structures. MIT
bVAE-IM (🥉8 · ⭐ 14 · 💀) - Implementation of Chemical Design with GPU-based Ising Machine. MIT QML single-paper
molecular-vae (🥉7 · ⭐ 71 · 💀) - Pytorch implementation of the paper Automatic Chemical Design Using a Data-Driven Continuous Representation of.. MIT rep-learn cheminformatics single-paper
cG-SchNet (🥉7 · ⭐ 70 · 💀) - cG-SchNet - a conditional generative neural network for 3d molecular structures. MIT
COATI (🥉6 · ⭐ 130 · 💀) - COATI: multi-modal contrastive pre-training for representing and traversing chemical space. Apache-2 drug-discovery multimodal pretrained rep-learn
rxngenerator (🥉6 · ⭐ 14 · 💀) - A generative model for molecular generation via multi-step chemical reactions. MIT
MolSLEPA (🥉5 · ⭐ 8 · 💀) - Interpretable Fragment-based Molecule Design with Self-learning Entropic Population Annealing. MIT XAI
Mapping out phase diagrams with generative classifiers (🥉4 · ⭐ 8 · 💀) - Repository for our ``Mapping out phase diagrams with generative models paper. MIT phase-transition
descriptors-inversion (🥉4 · ⭐ 6 · 💀) - Local inversion of the chemical environment representations. MIT rep-eng single-paper

Interatomic Potentials (ML-IAP)

Machine learning interatomic potentials (aka ML-IAP, MLIAP, MLIP, MLP) and force fields (ML-FF) for molecular dynamics.

fairchem (🥇31 · ⭐ 2.3K) - FAIR Chemistrys library of machine learning methods for chemistry. Formerly known as Open Catalyst Project. MIT pretrained UIP rep-learn catalysis

GitHub (👨‍💻 74 · 🔀 510 · 📋 610 - 1% open · ⏱️ 08.10.2026):
```
git clone https://github.com/FAIR-Chem/fairchem
```
PyPi (📥 19K / month · 📦 90 · ⏱️ 24.09.2026):
```
pip install fairchem-core
```

DeePMD-kit (🥇30 · ⭐ 2.1K) - A deep learning package for many-body potential energy representation and molecular dynamics. LGPL-3.0 MD workflows C++

GitHub (👨‍💻 94 · 🔀 640 · 📥 78K · 📦 63 · 📋 1.3K - 15% open · ⏱️ 06.10.2026):
```
git clone https://github.com/deepmodeling/deepmd-kit
```
PyPi (📥 17K / month · 📦 22 · ⏱️ 19.08.2026):
```
pip install deepmd-kit
```

Conda (📥 4.3K · ⏱️ 25.03.2025):

conda install -c deepmodeling deepmd-kit

Docker Hub (📥 7.4K · ⭐ 1 · ⏱️ 22.08.2026):
```
docker pull deepmodeling/deepmd-kit
```

NequIP (🥇27 · ⭐ 970) - NequIP is a code for building E(3)-equivariant interatomic potentials. MIT

GitHub (👨‍💻 46 · 🔀 210 · 📦 59 · 📋 130 - 4% open · ⏱️ 31.08.2026):
```
git clone https://github.com/mir-group/nequip
```
PyPi (📥 5.6K / month · 📦 29 · ⏱️ 01.09.2026):
```
pip install nequip
```
Conda (📥 35K · ⏱️ 05.09.2026):
```
conda install -c conda-forge nequip
```

TorchANI (🥇27 · ⭐ 560) - TorchANI 2.0 is an open-source library that supports training, development, and research of ANI-style neural network.. MIT

GitHub (👨‍💻 24 · 🔀 140 · 📦 85 · 📋 180 - 4% open · ⏱️ 06.09.2026):
```
git clone https://github.com/aiqm/torchani
```
PyPi (📥 4.5K / month · 📦 28 · ⏱️ 04.09.2026):
```
pip install torchani
```
Conda (📥 1.6M · ⏱️ 05.09.2026):
```
conda install -c conda-forge torchani
```

MatCalc (🥇25 · ⭐ 160) - A python library for calculating materials properties from the PES. BSD-3 workflows benchmarking UIP pretrained model-repository

GitHub (👨‍💻 24 · 🔀 38 · 📦 27 · 📋 48 - 8% open · ⏱️ 08.10.2026):
```
git clone https://github.com/materialsvirtuallab/matcalc
```
PyPi (📥 9.7K / month · 📦 14 · ⏱️ 07.10.2026):
```
pip install matcalc
```

MACE (🥇24 · ⭐ 1.4K) - MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing. MIT

GitHub (👨‍💻 83 · 🔀 470 · 📋 680 - 28% open · ⏱️ 07.10.2026):
```
git clone https://github.com/ACEsuit/mace
```

Metatrain (🥇24 · ⭐ 80) - Train, fine-tune, and manipulate machine learning models for atomistic systems. BSD-3 workflows benchmarking rep-eng rep-learn

GitHub (👨‍💻 44 · 🔀 42 · 📥 110 · 📦 18 · 📋 340 - 33% open · ⏱️ 08.10.2026):
```
git clone https://github.com/metatensor/metatrain
```
PyPi (📥 4.3K / month · 📦 6 · ⏱️ 25.09.2026):
```
pip install metatrain
```

janus-core (🥇21 · ⭐ 51) - Tools for machine learnt interatomic potentials. BSD-3 benchmarking workflows structure-optimization MD transport-phenomena

GitHub (👨‍💻 11 · 🔀 18 · 📥 270 · 📦 19 · 📋 320 - 17% open · ⏱️ 02.10.2026):
```
git clone https://github.com/stfc/janus-core
```
PyPi (📥 4K / month · 📦 9 · ⏱️ 02.10.2026):
```
pip install janus-core
```

TorchMD-NET (🥈19 · ⭐ 480) - Training neural network potentials. MIT MD rep-learn transformer pretrained

GitHub (👨‍💻 20 · 🔀 97 · 📥 230 · 📋 120 - 25% open · ⏱️ 13.07.2026):
```
git clone https://github.com/torchmd/torchmd-net
```

Conda (📥 1M · ⏱️ 18.03.2026):

conda install -c conda-forge torchmd-net

Autoplex (🥈18 · ⭐ 160 · 📉) - Code for automated fitting of machine learned interatomic potentials. GPL-3.0 benchmarking workflows

GitHub (👨‍💻 17 · 🔀 28 · 📦 2 · 📋 150 - 22% open · ⏱️ 06.10.2026):
```
git clone https://github.com/autoatml/autoplex
```
PyPi (📥 100 / month · ⏱️ 17.08.2026):
```
pip install autoplex
```

KLIFF (🥈18 · ⭐ 40 · 💤) - KIM-based Learning-Integrated Fitting Framework for interatomic potentials. LGPL-2.1 probabilistic workflows

GitHub (👨‍💻 14 · 🔀 21 · 📦 4 · 📋 56 - 41% open · ⏱️ 28.02.2026):
```
git clone https://github.com/openkim/kliff
```
PyPi (📥 82 / month · ⏱️ 11.04.2025):
```
pip install kliff
```
Conda (📥 260K · ⏱️ 06.09.2026):
```
conda install -c conda-forge kliff
```

Allegro (🥈17 · ⭐ 500) - Allegro is a code for building highly scalable E(3)-equivariant interatomic potentials. MIT

GitHub (👨‍💻 10 · 🔀 75 · 📦 5 · 📋 51 - 1% open · ⏱️ 28.05.2026):
```
git clone https://github.com/mir-group/allegro
```

Graph-PES (🥈16 · ⭐ 130) - train and use graph-based ML models of potential energy surfaces. MIT rep-learn UIP MD pretrained

GitHub (👨‍💻 8 · 🔀 16 · 📦 3 · 📋 19 - 26% open · ⏱️ 22.09.2026):
```
git clone https://github.com/jla-gardner/graph-pes
```
PyPi (📥 1.1K / month · 📦 2 · ⏱️ 22.09.2026):
```
pip install graph-pes
```

Pacemaker (🥈16 · ⭐ 120) - Python package for fitting atomic cluster expansion (ACE) potentials. Custom

GitHub (👨‍💻 9 · 🔀 27 · 📋 75 - 45% open · ⏱️ 04.09.2026):
```
git clone https://github.com/ICAMS/python-ace
```
PyPi (📥 210 / month · ⏱️ 04.09.2026):
```
pip install python-ace
```

wfl (🥈16 · ⭐ 43) - Workflow is a Python toolkit for building interatomic potential creation and atomistic simulation workflows. GPL-2.0 workflows HTC

GitHub (👨‍💻 21 · 🔀 21 · 📦 6 · 📋 170 - 42% open · ⏱️ 22.07.2026):
```
git clone https://github.com/libAtoms/workflow
```

apax (🥈16 · ⭐ 38) - A flexible and performant framework for training machine learning potentials. MIT

GitHub (👨‍💻 11 · 🔀 7 · 📦 7 · 📋 180 - 17% open · ⏱️ 01.06.2026):
```
git clone https://github.com/apax-hub/apax
```
PyPi (📥 130 / month · 📦 2 · ⏱️ 18.03.2026):
```
pip install apax
```

aiida-mlip (🥈16 · ⭐ 26) - machine learning interatomic potentials aiida plugin. BSD-3 workflows structure-optimization MD

GitHub (👨‍💻 10 · 🔀 14 · 📥 57 · 📦 4 · 📋 160 - 42% open · ⏱️ 02.10.2026):
```
git clone https://github.com/stfc/aiida-mlip
```
PyPi (📥 340 / month · ⏱️ 17.09.2026):
```
pip install aiida-mlip
```

PiNN (🥈15 · ⭐ 130) - A Python library for building atomic neural networks. BSD-3

GitHub (👨‍💻 9 · 🔀 41 · 📋 7 - 14% open · ⏱️ 17.09.2026):
```
git clone https://github.com/Teoroo-CMC/PiNN
```
Docker Hub (📥 1.2K · ⏱️ 17.09.2026):
```
docker pull teoroo/pinn
```

MLIPX - Machine-Learned Interatomic Potential eXploration (🥈15 · ⭐ 110 · 💤) - Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned.. MIT benchmarking viz workflows

GitHub (👨‍💻 5 · 🔀 8 · 📦 7 · 📋 18 - 33% open · ⏱️ 16.10.2025):
```
git clone https://github.com/basf/mlipx
```
PyPi (📥 2.4K / month · 📦 4 · ⏱️ 09.06.2025):
```
pip install mlipx
```

NNPOps (🥈15 · ⭐ 100 · 💤) - High-performance operations for neural network potentials. MIT MD C++

GitHub (👨‍💻 11 · 🔀 18 · 📋 67 - 41% open · ⏱️ 04.02.2026):
```
git clone https://github.com/openmm/NNPOps
```
Conda (📥 830K · ⏱️ 17.06.2026):
```
conda install -c conda-forge nnpops
```

Neural Force Field (🥈14 · ⭐ 290 · 💤) - Neural Network Force Field based on PyTorch. MIT pretrained

GitHub (👨‍💻 45 · 🔀 61 · 📋 23 - 21% open · ⏱️ 10.02.2026):
```
git clone https://github.com/learningmatter-mit/NeuralForceField
```

calorine (🥈13 · ⭐ 13) - A Python package for constructing and sampling neuroevolution potential models. https://doi.org/10.21105/joss.06264. Custom

PyPi (📥 2.4K / month · 📦 12 · ⏱️ 21.09.2026):
```
pip install calorine
```

GitLab (🔀 6 · 📋 140 - 6% open · ⏱️ 21.09.2026):

git clone https://gitlab.com/materials-modeling/calorine

DeepMD-GNN (🥈12 · ⭐ 56) - DeePMD-kit plugin for various graph neural network models. LGPL-3.0 rep-learn MD UIP C++

GitHub (👨‍💻 10 · 🔀 10 · 📋 30 - 20% open · ⏱️ 16.09.2026):
```
git clone https://github.com/deepmodeling/deepmd-gnn
```

TurboGAP (🥈12 · ⭐ 21) - The TurboGAP code. Custom Fortran

GitHub (👨‍💻 12 · 🔀 14 · 📋 12 - 25% open · ⏱️ 01.10.2026):
```
git clone https://github.com/mcaroba/turbogap
```

MACE-Jax (🥉11 · ⭐ 110) - Equivariant machine learning interatomic potentials in JAX. MIT

GitHub (👨‍💻 9 · 🔀 27 · 📋 12 - 50% open · ⏱️ 10.08.2026):
```
git clone https://github.com/ACEsuit/mace-jax
```

Asparagus (🥉11 · ⭐ 13) - Program Package for Sampling, Training and Applying ML-based Potential models https://doi.org/10.48550/arXiv.2407.15175. MIT workflows sampling MD

GitHub (👨‍💻 11 · 🔀 6 · ⏱️ 05.10.2026):
```
git clone https://github.com/MMunibas/Asparagus
```

tinker-hp (🥉10 · ⭐ 100) - Tinker-HP: High-Performance Massively Parallel Tinker for CPUs & GPUs. Custom

GitHub (👨‍💻 13 · 🔀 27 · 📋 29 - 24% open · ⏱️ 06.06.2026):
```
git clone https://github.com/TinkerTools/tinker-hp
```

MLXDM (🥉10 · ⭐ 9 · 📈) - A Neural Network Potential with Rigorous Treatment of Long-Range Dispersion https://doi.org/10.1039/D2DD00150K. MIT long-range

GitHub (👨‍💻 8 · 🔀 2 · ⏱️ 01.09.2026):
```
git clone https://github.com/RowleyGroup/MLXDM
```

PyNEP (🥉9 · ⭐ 71 · 💤) - A python interface of the machine learning potential NEP used in GPUMD. MIT

GitHub (👨‍💻 10 · 🔀 19 · 📋 14 - 42% open · ⏱️ 27.10.2025):
```
git clone https://github.com/bigd4/PyNEP
```

GAP (🥉9 · ⭐ 49) - Gaussian Approximation Potential (GAP). Custom

GitHub (👨‍💻 13 · 🔀 21 · ⏱️ 05.07.2026):
```
git clone https://github.com/libAtoms/GAP
```

ALF (🥉9 · ⭐ 47) - An open-source active learning framework for training machine-learned interatomic potentials. Custom active-learning

GitHub (👨‍💻 11 · 🔀 18 · 📋 2 - 50% open · ⏱️ 02.10.2026):
```
git clone https://github.com/lanl/alf
```

ACEfit (🥉9 · ⭐ 8 · 💤) - MIT Julia

GitHub (👨‍💻 10 · 🔀 8 · 📋 61 - 39% open · ⏱️ 20.03.2026):
```
git clone https://github.com/ACEsuit/ACEfit.jl
```

EquiformerV2 (🥉8 · ⭐ 350) - [ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations. MIT pretrained UIP rep-learn

GitHub (👨‍💻 2 · 🔀 49 · 📋 27 - 66% open · ⏱️ 10.04.2026):
```
git clone https://github.com/atomicarchitects/equiformer_v2
```

MatML (🥉5 · ⭐ 9) - Full MatML Docker image, including MatGL, MatCalc, MatPES and LAMMPS with ML-GNNP and ML-SNAP. BSD-3 MD UIP rep-learn pretrained

GitHub (👨‍💻 2 · 🔀 2 · ⏱️ 04.05.2026):

git clone https://github.com/materialsvirtuallab/matml

Docker Hub (📥 1.1K · ⭐ 2 · ⏱️ 08.04.2025):
```
docker pull materialsvirtuallab/matml
```

Show 44 hidden projects...

MEGNet (🥈20 · ⭐ 560 · 💀) - G