Comments (4)
ChandlerBang
commented on August 15, 2024
Hi, thanks for pointing this inconsistency out. It should be adj = (self.estimated_adj + self.estimated_adj.t())/2 and I have just fixed the issue. I also need to note that the default Pro-GNN hyper-parameter setting does not exert the symmetric constraint; so it does not affect the reported performance.
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zzysh12345
commented on August 15, 2024
Got it. But why doesn't the defualt setting exert the symmetric constraint,? It seems different from the paper. What effects will it have if using the constraint？
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ChandlerBang
commented on August 15, 2024
We treat this constraint as a hyper-parameter. And it turns out that without this constraint the performance is better.
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zzysh12345
commented on August 15, 2024
Got it. Thanks.
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Related Issues (20)
- The problem of graph adversarial attacks HOT 4
- why the cora dataset in deeprobust have 2485 nodes，and cora dataset in pyg have 2708 nodes? which one is correct? HOT 1
- How targeted_attack attack a subset of nodes? HOT 2
- The problem of NIPA HOT 1
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- Does deeprobust support ImageNet dataset and how to set parameters for attack algorithms when using it?
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- A source code error when using deeprobust.graph.data.Dataset under windows (have solved) HOT 3
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- Can this support GraphSAGE？
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