Diego-2504 / CGCNN_tutorialLinks
Crystal Graph Convolutional Neural Networks tutorial
☆31Updated 2 years ago
Alternatives and similar repositories for CGCNN_tutorial
Users that are interested in CGCNN_tutorial are comparing it to the libraries listed below
Sorting:
- DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules☆30Updated last year
- 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
- BAMBOO (Bytedance AI Molecular BOOster) is an AI-driven machine learning force field designed for precise and efficient electrolyte simu…☆146Updated 2 months ago
- Crystal Edge Graph Attention Neural Network☆23Updated last year
- The Bond valence site energy calculator☆21Updated 5 months ago
- A Curated Dataset of Crystal Structures and Experimentally Measured Ionic Conductivities for Lithium Solid-State Electrolytes☆46Updated 2 months ago
- ☆69Updated 4 years ago
- Tutorials related to GPUMD☆78Updated last month
- Defect structure-searching employing chemically-guided bond distortions☆112Updated last week
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆217Updated last week
- An E(3) equivariant Graph Neural Network for predicting electronic Hamiltonian matrix☆158Updated last week
- ☆118Updated this week
- SLICES: An Invertible, Invariant, and String-based Crystal Representation [2023, Nature Communications] MatterGPT, SLICES-PLUS☆138Updated 2 weeks ago
- GRACE models and gracemaker (as implemented in TensorPotential package)☆82Updated last month
- scripts to load all data from ICSD, Materials Project, and OQMD☆67Updated 3 years ago
- ☆45Updated 7 years ago
- ☆24Updated last year
- ☆26Updated last year
- Python library for the construction of porous materials using topology and building blocks.☆84Updated 8 months ago
- FTCP code☆36Updated 2 years ago
- A graph attention network based model for predicting atomic partial charges in metal-organic frameworks.☆13Updated 5 months ago
- This add-on to pymatgen provides tools for analyzing diffusion in materials.☆132Updated last week
- Composition-Conditioned Crystal GAN pytorch code☆42Updated 3 years ago
- Compiled binaries and sources of LAMMPS, redistributed by AdvanceSoft Corp.☆62Updated 7 months ago
- Machine Learning Interatomic Potential Predictions☆94Updated last year
- This is a conditionally generative model for crystal structures based on a modified version of CDVAE.☆39Updated 3 months ago
- LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials☆59Updated 4 months ago
- Code for automated fitting of machine learned interatomic potentials.☆134Updated last week
- AlphaCrytal: Contact map based deep learning algorithm for crystal structure prediction☆10Updated 2 years ago
- ☆63Updated last year