StellarGraph - Machine Learning on Graphs

Benchmark datasets, data loaders, and evaluators for graph machine learning

Precision Medicine Knowledge Graph (PrimeKG)

Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)

The integration of HugeGraph with AI/LLM & GraphRAG

A Python client for the Neo4j Graph Data Science (GDS) library

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

[ACL 2022] LinkBERT: A Knowledgeable Language Model 😎 Pretrained with Document Links

GraphXAI: Resource to support the development and evaluation of GNN explainers

Official repository for the paper "Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks" (ICLR 2022)

Applications and APIs from Oracle Graph

A curated list of graph data augmentation papers.

OpenABC-D is a large-scale labeled dataset generated by synthesizing open source hardware IPs. This dataset can be used for various graph level prediction problems in chip design.

Papers on Graph Analytics, Mining, and Learning

Official code for "vGraph: A Generative Model for Joint CommunityDetection and Node Representation Learning" (NeurIPS 2019)

Solutions to assignments of the CS224W Machine Learning with Graphs course from Stanford University.

Implementation of Directional Graph Networks in PyTorch and DGL

Author: Tong Zhao (tzhao2@nd.edu). ICML 2022. Learning from Counterfactual Links for Link Prediction

SignNet and BasisNet

Gigantic Graph Learning (GiGL) Framework: Large-scale training and inference for Graph Neural Networks