materialsvirtuallab / maml
Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
☆388Updated 2 weeks ago
Alternatives and similar repositories for maml:
Users that are interested in maml are comparing it to the libraries listed below
- Graph deep learning library for materials☆308Updated this week
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆412Updated 2 months ago
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆273Updated last month
- An open-source Python package for creating fast and accurate interatomic potentials.☆309Updated 2 weeks ago
- Jupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.☆237Updated 7 months ago
- An automatic engine for predicting materials properties.☆144Updated last year
- A code to generate atomic structure with symmetry☆294Updated this week
- atomate2 is a library of computational materials science workflows☆189Updated this week
- A Python package for manipulating atomistic data of software in computational science☆205Updated last week
- 🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.☆443Updated this week
- Matbench: Benchmarks for materials science property prediction☆142Updated 6 months ago
- Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ&hl=en https://www.youtube.com/watch?v=WYePj…☆251Updated 3 weeks ago
- atomate is a powerful software for computational materials science and contains pre-built workflows.☆250Updated 7 months ago
- n2p2 - A Neural Network Potential Package☆231Updated this week
- Things that you should (and should not) do in your Materials Informatics research.☆182Updated last year
- Materials science with Python at the atomic-scale☆201Updated 3 weeks ago
- The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field☆324Updated last week
- Curated list of known efforts in materials informatics, i.e. in modern materials science☆410Updated 5 months ago
- doped is a Python software for the generation, pre-/post-processing and analysis of defect supercell calculations, implementing the defec…☆159Updated this week
- A toolkit for visualizations in materials informatics.☆185Updated this week
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.☆624Updated this week
- ASAP is a package that can quickly analyze and visualize datasets of crystal or molecular structures.☆145Updated 7 months ago
- Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials☆371Updated 2 months ago
- i-PI: a universal force engine☆247Updated last month
- An evaluation framework for machine learning models simulating high-throughput materials discovery.☆130Updated this week
- Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.☆268Updated 2 weeks ago
- A data-driven method combining symbolic regression and compressed sensing for accurate & interpretable models.☆266Updated 2 weeks ago
- Deep neural networks for density functional theory Hamiltonian.☆259Updated 4 months ago
- New API client for the Materials Project☆127Updated this week
- Software for generating machine-learning interatomic potentials for LAMMPS☆161Updated last month