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.
☆217Updated last 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☆207Updated 4 months ago
- Build neural networks for machine learning force fields with JAX☆119Updated 3 weeks ago
- Neural Network Force Field based on PyTorch☆271Updated last month
- A plugin to use Nvidia GPU in PySCF package☆203Updated this week
- [ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations☆267Updated 3 months ago
- Torch-native, batchable, atomistic simulation.☆230Updated this week
- OpenEquivariance: a fast, open-source GPU JIT kernel generator for the Clebsch-Gordon Tensor Product.☆61Updated this week
- E3x is a JAX library for constructing efficient E(3)-equivariant deep learning architectures built on top of Flax.☆107Updated last month
- [ICLR 2024 Spotlight] Official Implementation of "Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Product…☆61Updated 7 months ago
- Equivariant machine learning interatomic potentials in JAX.☆72Updated last month
- A collection of QM data for training potential functions☆172Updated 3 months ago
- scalable molecular simulation☆136Updated 3 weeks ago
- Training neural network potentials☆406Updated 3 weeks ago
- Official implementation of All Atom Diffusion Transformers (ICML 2025)☆218Updated this week
- GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)☆200Updated 2 years ago
- [TMLR 2023] Training and simulating MD with ML force fields☆112Updated 7 months ago
- OpenMM plugin to define forces with neural networks☆199Updated 3 months ago
- sGDML - Reference implementation of the Symmetric Gradient Domain Machine Learning model☆148Updated last year
- An evaluation framework for machine learning models simulating high-throughput materials discovery.☆157Updated last week
- [ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs☆239Updated 3 months ago
- Boltzmann Generators and Normalizing Flows in PyTorch☆164Updated last year
- Higher order equivariant graph neural networks for 3D point clouds☆39Updated last year
- Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials☆399Updated last week
- Pytorch differentiable molecular dynamics☆176Updated 2 years ago
- Higher-order equivariant neural networks for charge density prediction in materials☆57Updated 3 months ago
- SO3krates and Universal Pairwise Force Field for Molecular Simulation☆103Updated last week
- repository and website for tutorials on 3d Euclidean equivariant neural networks☆71Updated 4 years ago
- MESS: Modern Electronic Structure Simulations☆30Updated 2 months ago
- ☆143Updated last week
- PySCF on IPU☆42Updated last year