profess-dev / profess-ad
PyTorch-based auto-differentiable orbital-free density functional theory package
☆12Updated 7 months ago
Related projects ⓘ
Alternatives and complementary repositories for profess-ad
- ☆16Updated 7 months ago
- ☆13Updated 3 weeks ago
- ☆30Updated 4 years 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
- python workflow toolkit☆35Updated last week
- Quick Uncertainty and Entropy via STructural Similarity☆30Updated last month
- Symmetry-Adapted Learning of Three-dimensional Electron Densities☆30Updated last week
- ☆41Updated 5 months ago
- Code for automated fitting of machine learned interatomic potentials.☆46Updated this week
- TB3Py: Two- and three-body tight-binding calculations for materials☆16Updated last month
- ☆43Updated 2 weeks ago
- Collection of tutorials to use the MACE machine learning force field.☆39Updated last month
- Machine Learning Interatomic Potentials with the Atomic Cluster Expansion☆49Updated 3 weeks ago
- Compute neighbor lists for atomistic systems☆25Updated last week
- Interactive Jupyter Notebooks for learning the fundamentals of Density-Functional Theory (DFT)☆59Updated last week
- Utility for applying the distortion symmetry method.☆28Updated 8 months ago
- Deep Modeling for Molecular Simulation, two-day virtual workshop, July 7-8, 2022☆49Updated 2 years ago
- ☆12Updated 6 months ago
- DeePTB: A deep learning package for tight-binding approach with ab initio accuracy.☆53Updated last month
- Computing representations for atomistic machine learning☆44Updated this week
- ☆40Updated 2 months ago
- Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics☆43Updated this week
- TheoDORE - A package for Theoretical Density, Orbital Relaxation and Exciton analysis☆30Updated 3 months ago
- Utility to construct and operate on Hamiltonians from the Projections of DFT wave functions on Atomic Orbital bases (PAO)☆22Updated 9 months ago
- PySCF with auto-differentiation☆68Updated this week
- ☆37Updated 2 weeks ago
- MAISE Module for Ab Initio Structure Evolution (MAISE)☆33Updated 3 months ago
- Official repository for the paper "Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials".☆12Updated 2 weeks ago
- Random symmetric initialization of crystals☆19Updated 6 years ago
- Some tutorial-style examples for validating machine-learned interatomic potentials☆28Updated 11 months ago