deepmodeling / CrystalFormer
Space Group Informed Transformer for Crystalline Materials Generation
☆55Updated 3 months ago
Related projects ⓘ
Alternatives and complementary repositories for CrystalFormer
- DeePTB: A deep learning package for tight-binding approach with ab initio accuracy.☆55Updated this week
- ☆78Updated last year
- ☆48Updated last month
- MACE-MP models☆47Updated last week
- Symmetry-Adapted Learning of Three-dimensional Electron Densities☆31Updated this week
- ☆41Updated 5 months ago
- Collection of tutorials to use the MACE machine learning force field.☆41Updated 2 months ago
- Code repository for a tutorial based on the "Direct prediction of phonon density of states with Euclidean neural networks"☆27Updated last year
- JADE-NAMD: An package for the on-the-fly nonadiabatic molecular dynamics simulation☆16Updated 3 years ago
- Integer Programming encoding for Crystal Structure Prediction with classic and quantum computing bindings☆42Updated last year
- ☆55Updated 6 months ago
- Advanced ASE Transition State Tools for ABACUS and Deep-Potential☆21Updated last month
- Deep Modeling for Molecular Simulation, two-day virtual workshop, July 7-8, 2022☆50Updated 2 years ago
- A python library for calculating materials properties from the PES☆66Updated 2 weeks ago
- python workflow toolkit☆36Updated 3 weeks ago
- Official implementation of DeepDFT model☆62Updated last year
- ☆72Updated this week
- Code for automated fitting of machine learned interatomic potentials.☆47Updated this week
- Extended DeepH (xDeepH) method for magnetic materials.☆33Updated last year
- ☆51Updated this week
- Interactive Jupyter Notebooks for learning the fundamentals of Density-Functional Theory (DFT)☆61Updated 2 weeks ago
- add the influence of external field to REANN model☆23Updated 2 months ago
- Generating Deep Potential with Python☆62Updated this week
- Solutions for Modern Quantum Chemistry, Szabo & Ostlund☆82Updated 2 years ago
- Document and code of python and PySCF approach XYG3 type of density functional 2nd-derivative realization☆59Updated 9 months ago
- Active learning workflow developed as a part of the upcoming article "Machine Learning Inter-Atomic Potentials Generation Driven by Activ…☆25Updated 3 years ago
- Utility to construct and operate on Hamiltonians from the Projections of DFT wfc on Atomic Orbital bases (PAO)☆37Updated last week
- Jupyter notebook for an introduction to atomic-scale machine learning class☆13Updated last year
- PyTorch-based auto-differentiable orbital-free density functional theory package☆12Updated 8 months ago