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The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"
Hi, qitian, when I download the cora dataset in "gen" folder and I found that all "gcn" initialized data features only correspon to 9 number of classes, while the 'gat' and 'sgc' have 10 number of classes. Could you please make a double check and maybe upload the right feature transformed data please?
Thanks for your kind help.
Dear EERM authors,
Thanks for sharing the code of this project. I really enjoy reading the paper!
There might be one spot that I misunderstand in your implementation and it would be really helpful if you could explain this line of code.
GraphOOD-EERM/temp_arxiv/main.py
Line 104 in ffdc4a1
My question lies in this line: shouldn't this line be ""m == args.T - 1"", as indicated in the Algorithm 1 in the paper.
I think the current implementation will not utilize the learned multiple environments (i.e., the parameter with shape K x N xN in the graph editor class) at all as the GNN will be updated before the graph editor does. And every time a new epoch starts the graph editors get reset.
Thanks in advance!
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