Open shirinmous opened 4 years ago
Hi, thanks for your interest. That's not surprising because we do not need expressive power in those node classification datasets. GIN is most useful when we really need expressive power (e.g., graph classification, or node classification with non-rich node features.)
Hi and thanks for sharing your code. When applying GIN to node classification task for example on cora dataset, the accuracy is low. You said in the paper that for mean aggregation and linear function GIN is GCN. I use the DGL implementation of GIN for node classification but I can't produce accuracy near to GCN. IS there a need for some preprocessing when applying GIN on node classification?
Would you please share the accuracy of your node classification on the cora dataset?
would you please tell me how to use the GIN on cora,I don't know how to load the data.
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Hi and thanks for sharing your code. When applying GIN to node classification task for example on cora dataset, the accuracy is low. You said in the paper that for mean aggregation and linear function GIN is GCN. I use the DGL implementation of GIN for node classification but I can't produce accuracy near to GCN. IS there a need for some preprocessing when applying GIN on node classification?