NVIDIA / cuEquivarianceLinks
cuEquivariance is a math library that is a collective of low-level primitives and tensor ops to accelerate widely-used models, like DiffDock, MACE, Allegro and NEQUIP, based on equivariant neural networks.
☆264Updated this week
Alternatives and similar repositories for cuEquivariance
Users that are interested in cuEquivariance are comparing it to the libraries listed below
Sorting:
- jax library for E3 Equivariant Neural Networks☆211Updated 6 months ago
- Torch-native, batchable, atomistic simulation.☆252Updated this week
- Build neural networks for machine learning force fields with JAX☆123Updated last month
- A collection of QM data for training potential functions☆178Updated 5 months ago
- OpenEquivariance: a fast, open-source GPU JIT kernel generator for the Clebsch-Gordon Tensor Product.☆80Updated last week
- Official implementation of All Atom Diffusion Transformers (ICML 2025)☆242Updated last month
- [ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations☆276Updated 5 months ago
- [ICLR 2024 Spotlight] Official Implementation of "Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Product…☆64Updated 8 months ago
- OpenMM plugin to define forces with neural networks☆201Updated 5 months ago
- Training neural network potentials☆423Updated last month
- Neural Network Force Field based on PyTorch☆276Updated last month
- A plugin to use Nvidia GPU in PySCF package☆213Updated this week
- E3x is a JAX library for constructing efficient E(3)-equivariant deep learning architectures built on top of Flax.☆109Updated 3 months ago
- [ICLR 2025] GotenNet: Rethinking Efficient 3D Equivariant Graph Neural Networks☆41Updated last month
- Pytorch differentiable molecular dynamics☆177Updated 2 years ago
- Implementation of the Euclidean fast attention (EFA) algorithm☆54Updated this week
- Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials☆413Updated this week
- Boltzmann Generators and Normalizing Flows in PyTorch☆170Updated last year
- repository and website for tutorials on 3d Euclidean equivariant neural networks☆72Updated 4 years ago
- scalable molecular simulation☆136Updated 3 weeks ago
- [TMLR 2023] Training and simulating MD with ML force fields☆112Updated 8 months ago
- sGDML - Reference implementation of the Symmetric Gradient Domain Machine Learning model☆153Updated last month
- Higher order equivariant graph neural networks for 3D point clouds☆40Updated 2 years ago
- [ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs☆243Updated 5 months ago
- This Denoising Force Field (DFF) codebase provides a Pytorch framework for the method presented in Two for one: Diffusion models and forc…☆62Updated last year
- Code for “From Molecules to Materials Pre-training Large Generalizable Models for Atomic Property Prediction”.☆59Updated 9 months ago
- A Library for Gaussian Processes in Chemistry☆237Updated 9 months ago
- Code for “FlowMM Generating Materials with Riemannian Flow Matching” and "FlowLLM: Flow Matching for Material Generation with Large Langu…☆151Updated 8 months ago
- Equivariant machine learning interatomic potentials in JAX.☆73Updated 3 months ago
- SO3krates and Universal Pairwise Force Field for Molecular Simulation☆105Updated last week