PASSIONLab / OpenEquivarianceLinks
OpenEquivariance: a fast, open-source GPU JIT kernel generator for the Clebsch-Gordon Tensor Product.
☆96Updated 3 weeks ago
Alternatives and similar repositories for OpenEquivariance
Users that are interested in OpenEquivariance are comparing it to the libraries listed below
Sorting:
- ☆23Updated last year
- Equivariant machine learning interatomic potentials in JAX.☆78Updated this week
- MESS: Modern Electronic Structure Simulations☆20Updated last year
- Compute neighbor lists for atomistic systems☆60Updated 2 weeks ago
- [NeurIPS'25 AI4Mat] Nequix: Training a foundation model for materials on a budget.☆46Updated this week
- Computing representations for atomistic machine learning☆74Updated 2 weeks ago
- Higher order equivariant graph neural networks for 3D point clouds☆45Updated 2 years ago
- A JAX-based Differentiable Density Functional Theory Framework for Materials☆37Updated this week
- Deprecated - see `pair_nequip_allegro`☆44Updated 6 months ago
- Particle-mesh based calculations of long-range interactions in PyTorch☆63Updated last week
- python library for atomistic machine learning☆89Updated last week
- ☆19Updated 2 years ago
- Build neural networks for machine learning force fields with JAX☆125Updated 4 months ago
- MESS: Modern Electronic Structure Simulations☆39Updated last month
- C++/CUDA library for SO(3) equivariant operations☆25Updated last week
- Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting☆35Updated last year
- LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials☆54Updated last month
- [NeurIPS 2024] Official implementation of the Efficiently Scaled Attention Interatomic Potential☆54Updated last month
- Pure C implementation of e3nn☆21Updated 7 months ago
- Official implementation of DeepDFT model☆84Updated 2 years ago
- ☆22Updated 5 months ago
- [npj Comp. Mat.] Higher-order equivariant neural networks for charge density prediction in materials☆65Updated 8 months ago
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆79Updated 3 years ago
- Training Neural Network potentials through customizable routines in JAX.☆52Updated 3 months ago
- Efficient And Fully Differentiable Extended Tight-Binding☆104Updated this week
- Collection of Tutorials on Machine Learning Interatomic Potentials☆23Updated last year
- pytorch implementation of dftd2 & dftd3 (not actively maintained)☆84Updated 11 months ago
- Particle-mesh based calculations of long-range interactions in JAX☆19Updated this week
- A framework for performing active learning for training machine-learned interatomic potentials.☆39Updated last month
- [TMLR 2025] Stability-Aware Training of Machine Learning Force Fields with Differentiable Boltzmann Estimators☆14Updated 8 months ago