pyGAT
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How to apply this model to extract graph features from multiple graphs?
Can I understand that the current dataset "cora" in the project only contains one graph, and how can I modify the code to utilize data from multiple graphs for training and generate overall graph embeddings?
Can I understand that the current dataset "cora" in the project only contains one graph, and how can I modify the code to utilize data from multiple graphs for training and generate overall graph embeddings?
As I understand it, GAT can only get embeddings for nodes. If you want to get full-graph embeddings, you need a graph pool method, such as diffpool
Can I understand that the current dataset "cora" in the project only contains one graph, and how can I modify the code to utilize data from multiple graphs for training and generate overall graph embeddings?
Do u know how to utilize data from multiple graphs for training now?
Can I understand that the current dataset "cora" in the project only contains one graph, and how can I modify the code to utilize data from multiple graphs for training and generate overall graph embeddings?
As I understand it, GAT can only get embeddings for nodes. If you want to get full-graph embeddings, you need a graph pool method, such as diffpool
The question is, now the model's input is like one graph, do I need to change the model' input or architecture?