rouyang2017 / SISSO
A data-driven method combining symbolic regression and compressed sensing for accurate & interpretable models.
☆266Updated 2 weeks ago
Alternatives and similar repositories for SISSO:
Users that are interested in SISSO are comparing it to the libraries listed below
- Python interface to the SISSO (Sure Independence Screening and Sparsifying Operator) method.☆53Updated 9 months ago
- doped is a Python software for the generation, pre-/post-processing and analysis of defect supercell calculations, implementing the defec…☆160Updated this week
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆273Updated last month
- 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
- Solvation model for the plane wave DFT code VASP.☆145Updated 7 months ago
- A Python package for manipulating atomistic data of software in computational science☆205Updated last week
- Graph deep learning library for materials☆308Updated this week
- This add-on to pymatgen provides tools for analyzing diffusion in materials.☆105Updated this week
- Automatic generation of crystal structure descriptions.☆110Updated last month
- Software for generating machine-learning interatomic potentials for LAMMPS☆161Updated last month
- A code to generate atomic structure with symmetry☆294Updated this week
- ASAP is a package that can quickly analyze and visualize datasets of crystal or molecular structures.☆145Updated 7 months ago
- Computational Materials Science(Book)☆80Updated 2 months ago
- Machine Learning Interatomic Potential Predictions☆89Updated last year
- ☆106Updated 2 years ago
- Repository for links to software packages and databases used in deep-learning applications for materials science☆136Updated 5 months ago
- Useful scripts for VASP☆185Updated 3 years ago
- Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.☆388Updated 2 weeks ago
- MLMD: a programming-free AI platform to predict and design materials☆59Updated last month
- Deep neural networks for density functional theory Hamiltonian.☆261Updated 4 months ago
- Catalyst Micro-kinetic Analysis Package for automated creation of micro-kinetic models used in catalyst screening☆99Updated 4 months ago
- Crystal Graph Convolutional Neural Networks tutorial☆23Updated last year
- automatic generation of LAMMPS input files for molecular dynamics simulations of MOFs☆141Updated last year
- Integer Programming encoding for Crystal Structure Prediction with classic and quantum computing bindings☆47Updated last year
- Kinetic Monte Carlo of Systems (KMCOS): lattice based kinetic Monte Carlo with a python front-end and Fortran back-end.☆19Updated 5 months ago
- The Materials Project Workshop Curriculum☆112Updated last year
- An open-source Python package for creating fast and accurate interatomic potentials.☆309Updated 2 weeks 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
- An E(3) equivariant Graph Neural Network for predicting electronic Hamiltonian matrix☆80Updated 2 weeks ago