GNN-CCA

Repository for benchmarking graph neural networks (JMLR 2023)

High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.

This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.

Python package for graph neural networks in chemistry and biology

A knowledge graph and a set of tools for drug repurposing

GraphGallery is a gallery for benchmarking Graph Neural Networks, From InplusLab.

Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric

Bag of Tricks for Graph Neural Networks.

Visualization tool for Graph Neural Networks

Open MatSci ML Toolkit is a framework for prototyping and scaling out deep learning models for materials discovery supporting widely used materials science datasets, and built on top of PyTorch Lightning, the Deep Graph Library, and PyTorch Geometric.