materialsvirtuallab / matgl
Graph deep learning library for materials
☆320Updated this week
Alternatives and similar repositories for matgl:
Users that are interested in matgl are comparing it to the libraries listed below
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆291Updated 2 months ago
- Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ&hl=en https://www.youtube.com/watch?v=WYePj…☆259Updated last month
- Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.☆402Updated this week
- Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.☆277Updated 2 weeks ago
- 🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.☆454Updated last week
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆156Updated this week
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆422Updated 3 months ago
- Matbench: Benchmarks for materials science property prediction☆147Updated 7 months ago
- An evaluation framework for machine learning models simulating high-throughput materials discovery.☆136Updated this week
- A toolkit for visualizations in materials informatics.☆197Updated this week
- atomate2 is a library of computational materials science workflows☆197Updated this week
- Jupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.☆240Updated 8 months ago
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.☆652Updated this week
- An automatic engine for predicting materials properties.☆152Updated last year
- A code to generate atomic structure with symmetry☆302Updated this week
- An open-source Python package for creating fast and accurate interatomic potentials.☆312Updated last month
- doped is a Python software for the generation, pre-/post-processing and analysis of defect supercell calculations, implementing the defec…☆168Updated last week
- MatDeepLearn, package for graph neural networks in materials chemistry☆184Updated 2 years ago
- ASAP is a package that can quickly analyze and visualize datasets of crystal or molecular structures.☆144Updated 8 months ago
- This add-on to pymatgen provides tools for analyzing diffusion in materials.☆109Updated this week
- n2p2 - A Neural Network Potential Package☆234Updated this week
- New API client for the Materials Project☆130Updated 2 weeks ago
- atomate is a powerful software for computational materials science and contains pre-built workflows.☆251Updated 8 months ago
- Neural Network Force Field based on PyTorch☆267Updated last month
- An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]☆283Updated 7 months ago
- molSimplify code☆183Updated this week
- NequIP is a code for building E(3)-equivariant interatomic potentials☆693Updated last month
- Deep neural networks for density functional theory Hamiltonian.☆271Updated 5 months ago
- A Python package for manipulating atomistic data of software in computational science☆207Updated this week
- MSE5540/6640 Materials Informatics course at the University of Utah. Learn how data science tools are revolutionizing materials science!☆138Updated this week