mir-group / pair_nequipLinks
Deprecated - see `pair_nequip_allegro`
☆44Updated 7 months ago
Alternatives and similar repositories for pair_nequip
Users that are interested in pair_nequip are comparing it to the libraries listed below
Sorting:
- Computing representations for atomistic machine learning☆74Updated 2 weeks ago
- Collection of tutorials to use the MACE machine learning force field.☆50Updated last year
- python workflow toolkit☆45Updated this week
- KIM-based Learning-Integrated Fitting Framework for interatomic potentials.☆39Updated this week
- Particle-mesh based calculations of long-range interactions in PyTorch☆64Updated last month
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆80Updated 3 years ago
- Quick Uncertainty and Entropy via STructural Similarity☆50Updated last week
- ☆108Updated this week
- ☆31Updated 2 months ago
- DeePMD-kit plugin for various graph neural network models☆51Updated this week
- Official implementation of DeepDFT model☆85Updated 2 years ago
- LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials☆58Updated 2 months ago
- Compute neighbor lists for atomistic systems☆68Updated 3 weeks ago
- Active Learning for Machine Learning Potentials☆62Updated 2 weeks ago
- A framework for performing active learning for training machine-learned interatomic potentials.☆39Updated 3 weeks ago
- JAX-ReaxFF: A Gradient Based Framework for Extremely Fast Optimization of Reactive Force Fields☆71Updated last year
- UF3: a python library for generating ultra-fast interatomic potentials☆68Updated 5 months ago
- Symmetry-Adapted Learning of Three-dimensional Electron Densities (and their electrostatic response)☆40Updated last month
- Train, fine-tune, and manipulate machine learning models for atomistic systems☆50Updated last week
- A Python software package for saddle point optimization and minimization of atomic systems.☆120Updated 2 months ago
- Code for automated fitting of machine learned interatomic potentials.☆131Updated 3 weeks ago
- A scalable and versatile library to generate representations for atomic-scale learning☆82Updated last year
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆96Updated this week
- Official repository for the paper "Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials".☆21Updated last year
- Equivariant machine learning interatomic potentials in JAX.☆80Updated last week
- Basis set optimization library for quantum chemistry☆35Updated 5 months ago
- Deep Modeling for Molecular Simulation, two-day virtual workshop, July 7-8, 2022☆53Updated 3 years ago
- Efficient And Fully Differentiable Extended Tight-Binding☆109Updated this week
- Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting☆36Updated last year
- ☆31Updated last week