GNN-Learning-and-Integration

An Industrial Graph Neural Network Framework

An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)

Code and resources on scalable and efficient Graph Neural Networks (TNNLS 2023)

A PyTorch Graph Neural Network Library

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

1. Use BERT, ALBERT and GPT2 as tensorflow2.0's layer. 2. Implement GCN, GAN, GIN and GraphSAGE based on message passing.

[NeurIPS'22] Tokenized Graph Transformer (TokenGT), in PyTorch

SPIGA: Shape Preserving Facial Landmarks with Graph Attention Networks.

PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)