StellarGraph - Machine Learning on Graphs

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

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

Precision Medicine Knowledge Graph (PrimeKG)

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

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

A curated list of graph data augmentation papers.

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

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)

Papers on Graph Analytics, Mining, and Learning

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.

Implementation of Directional Graph Networks in PyTorch and DGL

TigerLily: Finding drug interactions in silico with the Graph.

SignNet and BasisNet

Given an input graph (ArangoDB or PyG) it generates graph embeddings using Low-Code framework built on top of PyG.

Author: Tong Zhao ([email protected]). ICML 2022. Learning from Counterfactual Links for Link Prediction

The integration of HugeGraph with AI/LLM & GraphRAG

Applications using Parallel Graph AnalytiX (PGX) from Oracle Labs

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