uw-cmg / MAST-MLLinks
MAterials Simulation Toolkit for Machine Learning (MAST-ML)
☆125Updated 5 months ago
Alternatives and similar repositories for MAST-ML
Users that are interested in MAST-ML are comparing it to the libraries listed below
Sorting:
- Data Science for Materials Science☆64Updated 2 weeks ago
- Deep Learning the Chemistry of Materials From Only Elemental Composition for Enhancing Materials Property Prediction☆97Updated 2 years ago
- Code to help you get started using machine learning in materials science☆17Updated 6 years ago
- A machine learning environment for atomic-scale modeling in surface science and catalysis.☆115Updated last year
- An automatic engine for predicting materials properties.☆163Updated last year
- Expanded dataset of mechanical properties and observed phases of multi-principal element alloys☆36Updated 3 years ago
- Automatic generation of crystal structure descriptions.☆124Updated last week
- This repository is no longer maintained. For the latest updates and continued development, please visit: https://github.com/atomgptlab/ja…☆90Updated 2 months ago
- Deep learning for crystal-structure recognition and analysis of atomic structures☆43Updated last year
- Machine Learning Interatomic Potential Predictions☆93Updated last year
- ☆70Updated 4 years ago
- ☆104Updated last month
- This add-on to pymatgen provides tools for analyzing diffusion in materials.☆125Updated 2 weeks ago
- Repository for spectral neighbor analysis potential (SNAP) model development.☆36Updated 5 years ago
- A Python library to calculate elastic properties of materials.☆59Updated last month
- The Materials Project Workshop Curriculum☆116Updated 2 years ago
- The materials for the Fall ML in Materials course at the UTK MSE☆87Updated last year
- Python package to aid materials design and informatics☆121Updated 2 weeks ago
- pyiron_atomistics - an integrated development environment (IDE) for atomistic simulation in computational materials science.☆47Updated last week
- 3-D Inorganic Crystal Structure Generation and Property Prediction via Representation Learning (JCIM 2020)☆41Updated 2 years ago
- First-principles statistical mechanical software for the study of multi-component crystalline solids☆115Updated last year
- Deep learning framework for atomistic image data☆34Updated 3 weeks ago
- ☆95Updated this week
- Agent-based sequential learning software for materials discovery☆63Updated last year
- Tutorials for using the pymatgen library☆55Updated 3 months ago
- A Python library for building atomic neural networks☆117Updated 5 months ago
- Python Materials Discovery Framework☆75Updated last year
- Python library written in C++ for calculation of local atomic structural environment☆67Updated last year
- A Python library and command line interface for automated free energy calculations☆82Updated last month
- Predict materials properties using only the composition information!☆109Updated 2 years ago