Jhy1993 / HANLinks
Heterogeneous Graph Neural Network
☆1,143Updated 5 years ago
Alternatives and similar repositories for HAN
Users that are interested in HAN are comparing it to the libraries listed below
Sorting:
- A PyTorch implementation of GraphSAGE. This package contains a PyTorch implementation of GraphSAGE.☆652Updated last year
- code of HetGNN☆406Updated 5 years ago
- Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric☆841Updated last year
- Representation-Learning-on-Heterogeneous-Graph☆441Updated 5 years ago
- Implementation and experiments of graph neural netwokrs, like gcn,graphsage,gat,etc.☆817Updated 2 years ago
- Simple reference implementation of GraphSAGE.☆1,022Updated 5 years ago
- Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding☆421Updated 4 years ago
- Code for EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs☆567Updated 3 years ago
- ICLR 2020: Composition-Based Multi-Relational Graph Convolutional Networks☆620Updated 10 months ago
- Keras implementation of the graph attention networks (GAT) by Veličković et al. (2017; https://arxiv.org/abs/1710.10903)☆488Updated 4 years ago
- CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)☆1,783Updated last year
- Deep Graph Infomax (https://arxiv.org/abs/1809.10341)☆642Updated 2 years ago
- Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)☆1,029Updated 2 years ago
- gnn explainer☆967Updated 9 months ago
- Source code and dataset for KDD 2019 paper "Representation Learning for Attributed Multiplex Heterogeneous Network"☆531Updated 3 years ago
- Implementation of R-GCNs for Relational Link Prediction☆457Updated 2 years ago
- This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification☆472Updated 2 years ago
- This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.☆920Updated 4 months ago
- official implementation for the paper "Simplifying Graph Convolutional Networks"☆843Updated 3 years ago
- How Powerful are Graph Neural Networks?☆1,219Updated 3 years ago
- Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"☆492Updated 10 months ago
- Semi-supervised learning with graph embeddings☆921Updated 5 years ago
- A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).☆799Updated 2 years ago
- Efficient and Friendly Graph Neural Network Library for TensorFlow 1.x and 2.x☆505Updated 5 months ago
- Archive of Temporal Knowledge Reasoning in Social Network and Knowledge Graph☆444Updated last year
- resources for graph convolutional networks (图卷积神经网络相关资源)☆899Updated 5 years ago
- PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.☆1,199Updated 2 months ago
- Materials for DGL hands-on tutorial in WWW 2020☆504Updated 4 years ago
- Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks.☆325Updated last year
- Heterogeneous Network Embedding: Survey, Benchmark, Evaluation, and Beyond☆258Updated 4 years ago