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Hi, I have read and tried the codes, and now it can work on my graph-level GNN model in multi-instance case.
The input graph in my project is a spatiotemporal graph, which connects the subgraph in each frame together as a whole graph.
Then I realize the difference between my project and the applications of GNNExplainer. The labels used in GNNExplainer are the node labels, while I am more interested to explain the relation between the GNN model and the whole graph’s label.
Is it possible that if I change the label in GNNExplainer to the graph label, can GNNExplainer then generate a meaningful explanation? Considering the mutual information in GNNExplainer, I think it can work, but I am not confident enough.
Could someone please give me some advice? This will be very helpful.
I'm also trying to use GNNExplainer for the graph regression task. However, instead of finding existing edges in the graph, GNNExplainer generates new edges. For example, I have a subgraph with 238 nodes and 154 edges that GNNExplainer finds; just nine edges exist in the accurate graph.
Did you ever experience the same issue? I would be happy to hear your suggestions! @RexYing@hnaik
Hi, I have read and tried the codes, and now it can work on my graph-level GNN model in multi-instance case.
The input graph in my project is a spatiotemporal graph, which connects the subgraph in each frame together as a whole graph.
Then I realize the difference between my project and the applications of GNNExplainer. The labels used in GNNExplainer are the node labels, while I am more interested to explain the relation between the GNN model and the whole graph’s label.
Is it possible that if I change the label in GNNExplainer to the graph label, can GNNExplainer then generate a meaningful explanation? Considering the mutual information in GNNExplainer, I think it can work, but I am not confident enough.
Could someone please give me some advice? This will be very helpful.
@RexYing @hnaik
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