RishikeshMagar / OGCNNLinks
Crystal graph convolutional neural networks for predicting material properties.
☆34Updated 3 years ago
Alternatives and similar repositories for OGCNN
Users that are interested in OGCNN are comparing it to the libraries listed below
Sorting:
- Representation Learning from Stoichiometry☆59Updated 2 years ago
- Crystal Edge Graph Attention Neural Network☆24Updated last year
- ☆34Updated last year
- Python library for the construction of porous materials using topology and building blocks.☆79Updated 6 months ago
- FTCP code☆35Updated 2 years ago
- scripts to load all data from ICSD, Materials Project, and OQMD☆68Updated 3 years ago
- GRACE models and gracemaker (as implemented in TensorPotential package)☆76Updated 2 weeks ago
- ☆108Updated this week
- Official implementation of DeepDFT model☆85Updated 2 years ago
- ☆23Updated last year
- A system for rapid identification and analysis of metal-organic frameworks☆63Updated last year
- LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials☆58Updated 2 months ago
- Metadynamics code on the G-space.☆14Updated 3 years ago
- Composition-Conditioned Crystal GAN pytorch code☆43Updated 3 years ago
- Code for automated fitting of machine learned interatomic potentials.☆131Updated 2 weeks ago
- ☆26Updated last year
- 3-D Inorganic Crystal Structure Generation and Property Prediction via Representation Learning (JCIM 2020)☆41Updated 2 years ago
- This is a simple but efficient implementation of PaiNN-model for constructing machine learning interatomic potentials☆23Updated 3 years ago
- Generate and predict molecular electron densities with Euclidean Neural Networks☆48Updated 2 years ago
- Calculate Spectrum Based on Fast Fourier Transform (FFT) of the Velocity Autocorrelation Function (VACF).☆28Updated 2 years ago
- Machine Learning Interatomic Potential Predictions☆94Updated last year
- Integer Programming encoding for Crystal Structure Prediction with classic and quantum computing bindings☆48Updated 2 years ago
- Original implementation of CSPML☆28Updated 11 months ago
- ☆29Updated 3 years ago
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆80Updated 3 years ago
- We developed a novel method, MOF-CGCNN, to efficiently and accurately predict the methane the volumetric uptakes at 65 bar for MOFs. Two …☆21Updated 4 years ago
- DistMLIP: A Distributed Inference Library for Fast, Large Scale Atomistic Simulation☆89Updated 2 months ago
- ☆34Updated 3 years ago
- Python package to interact with high-dimensional representations of the chemical elements☆46Updated last week
- train and use graph-based ML models of potential energy surfaces☆114Updated this week