Shypd.aiThe largest open index of AI toolsHAN is an open-source Research & Education tool that provides the source code for Heterogeneous Graph Attention Networks. It is designed for representation learning on heterogeneous graphs, building upon the GAT model.
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HAN offers the source code for implementing and experimenting with Heterogeneous Graph Attention Networks, a model specifically designed for representation learning on heterogeneous graphs. Based on the GAT model, HAN enables researchers and developers to delve into advanced graph neural network architectures. The tool supports various tasks such as node classification and link prediction, making it valuable for academic research in graph theory and machine learning. It provides preprocessed datasets for DBLP, ACM, and IMDB, facilitating quick setup and experimentation. The project also includes detailed documentation on data preprocessing and running experiments, making it accessible for those working with complex graph structures.
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