Crystal Edge Graph Attention Neural Network
☆23Jun 17, 2024Updated last year
Alternatives and similar repositories for CEGANN
Users that are interested in CEGANN are comparing it to the libraries listed below
Sorting:
- ☆15Oct 8, 2023Updated 2 years ago
- A graph attention network based model for predicting atomic partial charges in metal-organic frameworks.☆13Aug 26, 2025Updated 6 months ago
- A Continuous Action Space Tree search for INverse desiGn (CASTING)☆15Dec 8, 2023Updated 2 years ago
- Deep Learning Analysis of Defect and Phase Evolution During Electron Beam Induced Transformations in WS2☆13Aug 14, 2018Updated 7 years ago
- Tutorials for DeepModeling projects.☆16Apr 3, 2025Updated 11 months ago
- Crystal graph convolutional neural networks for predicting material properties.☆33Nov 9, 2022Updated 3 years ago
- ☆19Jul 1, 2023Updated 2 years ago
- Repository for UCSD NANO 266 Quantum Mechanical Modelling of Materials☆22Nov 13, 2024Updated last year
- CrysXPP: An Explainable Property Predictor for Crystalline Materials (NPJ Computational Materials - 2022)☆21Jul 4, 2023Updated 2 years ago
- ☆16Jan 22, 2026Updated last month
- Veidt is a deep learning library for materials science.☆18May 5, 2020Updated 5 years ago
- Supplementary Data for "A graph representation of molecular ensembles for polymer property prediction"☆22Oct 12, 2022Updated 3 years ago
- A DGL implementation of "Directional Message Passing for Molecular Graphs" (ICLR 2020).☆21Oct 21, 2023Updated 2 years ago
- Crystallography Companion Agent☆21Jul 8, 2022Updated 3 years ago
- ☆19Sep 23, 2025Updated 5 months ago
- Pytorch Repository for our work: Graph convolutional neural networks with global attention for improved materials property prediction☆84Dec 17, 2024Updated last year
- ☆28Aug 14, 2022Updated 3 years ago
- Crystal Graph Convolutional Neural Networks tutorial☆31Mar 27, 2023Updated 2 years ago
- Software tools for fragment-based drug discovery (FBDD)☆27Apr 6, 2020Updated 5 years ago
- DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules☆30Jan 3, 2025Updated last year
- ☆31Aug 3, 2021Updated 4 years ago
- Crystal graph attention neural networks for materials prediction☆31Jul 18, 2023Updated 2 years ago
- cp2k test☆10May 26, 2019Updated 6 years ago
- Ramirez Lab WIKI, where you could find Tutorials, Script Library, Gallery, FAQ, and a little bit more☆13Sep 11, 2024Updated last year
- Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals☆551Apr 27, 2023Updated 2 years ago
- A software for mapping energy landscape with a variety of methods, using classical potentials. Based on the LAMMPS MD package.☆11Jan 29, 2021Updated 5 years ago
- This is the repository of code and data for paper "Machine learning-enabled chemical space exploration of all-inorganic perovskites for p…☆10Sep 23, 2024Updated last year
- ☆12Nov 7, 2022Updated 3 years ago
- Python module for identification of conserved water molecules from molecular dynamics trajectories.☆14Feb 12, 2026Updated 3 weeks ago
- Fast estimation of ion-pairing for screening electrolytes☆11Aug 23, 2022Updated 3 years ago
- Atom-by-atom design of metal oxide catalysts for the oxygen evolution reaction with Machine Learning☆10Oct 19, 2023Updated 2 years ago
- Benchmarking of 1D pattern classification networks☆10Jul 19, 2023Updated 2 years ago
- BERTOS: transformer for oxidation state prediction☆15Apr 18, 2025Updated 10 months ago
- This program computes the sum-frequency generation (SFG) spectrum for a give MD trajectory of interfacial water molecules. The program ca…☆12Jul 24, 2023Updated 2 years ago
- ☆34Jul 14, 2024Updated last year
- Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.☆448Updated this week
- ☆38Dec 16, 2021Updated 4 years ago
- Data, in citable form, produced by the Coudert research group☆45Feb 3, 2026Updated last month
- Crystal graph convolutional neural networks for predicting material properties.☆825Sep 6, 2021Updated 4 years ago