Search Packages

torch-geometric

Graph Neural Network Library for PyTorch

openequivariance

OpenEquivariance: a fast, open-source GPU JIT kernel generator for the Clebsch-Gordon Tensor Product.

pyg-nightly

Graph Neural Network Library for PyTorch

dgllife

Python package for graph neural networks in chemistry and biology

torch-cluster

PyTorch Extension Library of Optimized Graph Cluster Algorithms

pypose

A library for differentiable robotics on manifolds.

torch-spline-conv

Implementation of the Spline-Based Convolution Operator of SplineCNN in PyTorch

sphericart

Multi-language library for the calculation of spherical harmonics in Cartesian coordinates

sphericart-torch

Multi-language library for the calculation of spherical harmonics in Cartesian coordinates

graphein

Protein Graph Library

escnn

Equivariant Steerable CNNs Library for Pytorch https://quva-lab.github.io/escnn/

neuralogic

PyNeuraLogic lets you use Python to create Differentiable Logic Programs

sphericart-jax

Multi-language library for the calculation of spherical harmonics in Cartesian coordinates

stellargraph

StellarGraph - Machine Learning on Graphs

avitai-artifex

A research-focused modular generative modeling library built on JAX/Flax NNX

vn-transformer

A Transformer made of Rotation-equivariant Attention using Vector Neurons

cellshape

3D shape analysis using deep learning

graphgallery

GraphGallery is a gallery for benchmarking Graph Neural Networks

deltaconv

Implementation of DeltaConv: an anisotropic operator for geometric deep learning on point clouds (and other discretizations that will be added in the future).

ptgnn

A PyTorch Graph Neural Network Library

nx-yaml

YAML as a human-readable Hypergraph Interchange Format (HIF) for NetworkX

aidsorb

Python package for deep learning on molecular point clouds.

openequivariance-extjax

OpenEquivariance: a fast, open-source GPU JIT kernel generator for the Clebsch-Gordon Tensor Product.

dhl-mm

Up to 913x faster Lie algebra products for all five exceptional algebras with differentiable PyTorch equivariant layers