🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
☆641Apr 16, 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:
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.☆1,145Apr 6, 2026Updated last week
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆241Updated this week
- Torch-native, batchable, atomistic simulations.☆446Updated this week
- An evaluation framework for machine learning models simulating high-throughput materials discovery.☆221Updated this week
- A collection of Neural Network Models for chemistry☆187Apr 9, 2026Updated last week
- Serverless GPU API endpoints on Runpod - Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Compute neighbor lists for atomistic systems☆74Apr 10, 2026Updated last week
- A toolkit for visualizations in materials informatics.☆309Apr 9, 2026Updated last week
- ORB forcefield models from Orbital Materials☆567Mar 18, 2026Updated last month
- NequIP is a code for building E(3)-equivariant interatomic potentials☆895Mar 25, 2026Updated 3 weeks ago
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆378Feb 19, 2026Updated last month
- Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.☆453Apr 6, 2026Updated last week
- train and use graph-based ML models of potential energy surfaces☆122Mar 9, 2026Updated last month
- FAIR Chemistry's library of machine learning methods for chemistry☆2,055Updated this week
- quacc is a flexible platform for computational materials science and quantum chemistry that is built for the big data era.☆256Apr 6, 2026Updated last week
- Simple, predictable pricing with DigitalOcean hosting • AdAlways know what you'll pay with monthly caps and flat pricing. Enterprise-grade infrastructure trusted by 600k+ customers.
- Code for automated fitting of machine learned interatomic potentials.☆144Apr 9, 2026Updated last week
- 🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics …☆95Apr 12, 2026Updated last week
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆101Jan 28, 2026Updated 2 months ago
- A python library for calculating materials properties from the PES☆137Updated this week
- scalable molecular simulation☆141Mar 30, 2026Updated 2 weeks ago
- Training neural network potentials☆472Mar 31, 2026Updated 2 weeks ago
- Graph deep learning library for materials☆535Updated this week
- A Python package for estimating diffusion properties from molecular dynamics simulations.☆80Apr 8, 2026Updated last week
- atomate2 is a library of computational materials science workflows☆296Updated this week
- GPUs on demand by Runpod - Special Offer Available • AdRun AI, ML, and HPC workloads on powerful cloud GPUs—without limits or wasted spend. Deploy GPUs in under a minute and pay by the second.
- Curated list of known efforts in materials informatics, i.e. in modern materials science☆503Mar 24, 2026Updated 3 weeks ago
- End-To-End Molecular Dynamics (MD) Engine using PyTorch☆696Jan 7, 2026Updated 3 months ago
- MatterSim: A deep learning atomistic model across elements, temperatures and pressures.☆529Apr 7, 2026Updated last week
- A code to generate atomic structure with symmetry☆360Apr 7, 2026Updated last week
- Computing representations for atomistic machine learning☆80Apr 2, 2026Updated 2 weeks ago
- Library for Crystal Symmetry in Rust☆70Updated this week
- GRACE models and gracemaker (as implemented in TensorPotential package)☆89Mar 6, 2026Updated last month
- SchNetPack - Deep Neural Networks for Atomistic Systems☆914Apr 10, 2026Updated last week
- An open-source Python package for creating fast and accurate interatomic potentials.☆351Feb 6, 2026Updated 2 months ago
- Wordpress hosting with auto-scaling - Free Trial • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Build neural networks for machine learning force fields with JAX☆136Jun 2, 2025Updated 10 months ago
- Universal interatomic potentials for advanced materials modeling☆196Mar 31, 2026Updated 2 weeks ago
- Train, fine-tune, and manipulate machine learning models for atomistic systems☆65Updated this week
- Neural Network Force Field based on PyTorch☆289Feb 10, 2026Updated 2 months ago
- Alchemical machine learning interatomic potentials☆34Nov 8, 2024Updated last year
- Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials☆472Mar 4, 2026Updated last month
- Python module for drawing and rendering beautiful atoms and molecules using Blender.☆190Dec 9, 2025Updated 4 months ago