Graph deep learning library for materials
☆578Sep 30, 2026Updated last week
Alternatives and similar repositories for matgl
Users that are interested in matgl are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆413Sep 15, 2026Updated 3 weeks ago
- A python library for calculating materials properties from the PES☆157Updated this week
- Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.☆332Apr 7, 2025Updated last year
- A toolkit for visualizations in materials informatics.☆336Oct 3, 2026Updated last week
- An evaluation framework for machine learning models simulating high-throughput materials discovery.☆255Oct 3, 2026Updated last week
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆277Updated this week
- A foundational potential energy dataset for materials☆61Aug 4, 2026Updated 2 months ago
- Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.☆466Oct 5, 2026Updated last week
- atomate2 is a library of computational materials science workflows☆354Updated this week
- MatterSim: A deep learning atomistic model across elements, temperatures and pressures.☆602Aug 20, 2026Updated last month
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.☆1,386Updated this week
- Torch-native, batchable, atomistic simulations.☆502Oct 6, 2026Updated last week
- Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals☆558Apr 27, 2023Updated 3 years ago
- Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ https://www.youtube.com/@dr_k_choudhary☆334Aug 25, 2025Updated last year
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]☆380Aug 14, 2024Updated 2 years ago
- ORB forcefield models from Orbital Materials☆622Sep 26, 2026Updated 2 weeks ago
- GRACE models and gracemaker (as implemented in TensorPotential package)☆106Sep 3, 2026Updated last month
- Crystal graph convolutional neural networks for predicting material properties.☆894Sep 6, 2021Updated 5 years ago
- FAIR Chemistry's library of machine learning methods for chemistry☆2,287Updated this week
- MACE foundation models (MP, OMAT, mh-1)☆314Aug 26, 2026Updated last month
- NequIP is a code for building E(3)-equivariant interatomic potentials☆970Sep 30, 2026Updated last week
- Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support f…☆1,991Oct 4, 2026Updated last week
- quacc is a flexible platform for computational materials science and quantum chemistry that is built for the big data era.☆298Oct 6, 2026Updated last week
- End-to-end encrypted cloud storage - Proton Drive • AdSpecial offer: 40% Off Yearly / 80% Off First Month. Protect your most important files, photos, and documents from prying eyes.
- A code to generate atomic structure with symmetry☆393Oct 6, 2026Updated last week
- 🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.☆727Updated this week
- Data mining for materials science☆617Oct 5, 2026Updated last week
- doped is a Python software for the generation, pre-/post-processing and analysis of defect supercell calculations, implementing the defec…☆283Updated this week
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆474Apr 18, 2026Updated 5 months ago
- A Large Language Model of the CIF format for Crystal Structure Generation☆167Mar 16, 2026Updated 6 months ago
- Generative materials benchmarking metrics, inspired by guacamol and CDVAE.☆41Jun 1, 2024Updated 2 years ago
- Code for automated fitting of machine learned interatomic potentials.☆162Oct 6, 2026Updated last week
- DistMLIP: A Distributed Inference Library for Fast, Large Scale Atomistic Simulation☆99Sep 20, 2025Updated last year
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- Interactive browser visualizations for materials science: crystal structures/molecules, trajectories, convex hulls, phase diagrams, Fermi…☆364Updated this week
- An E(3) equivariant Graph Neural Network for predicting electronic Hamiltonian matrix☆226Sep 18, 2026Updated 3 weeks ago
- Matbench: Benchmarks for materials science property prediction☆220Aug 20, 2024Updated 2 years ago
- train and use graph-based ML models of potential energy surfaces☆130Sep 22, 2026Updated 3 weeks ago
- 🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics …☆109Jul 2, 2026Updated 3 months ago
- Official code for Periodic Graph Transformers for Crystal Material Property Prediction (NeurIPS 2022)☆114Dec 15, 2023Updated 2 years ago
- ☆115Sep 4, 2026Updated last month