KGNET

Neo4j graph construction from unstructured data using LLMs

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)

Medical Graph RAG: Graph RAG for the Medical Data

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).

Connect your AI app directly to your data with a full stack solution. Fully connected Agentic Graph RAG pipelines mean you can focus on fine tuning your app and not building data infrastructure.

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.