Comments (8)
Hello,
I'm not sure I understand your question. We use standard benchmark datasets for all experiments reported in our paper. For example, Cora, Citeseer and Pubmed can all be found in Thomas Kipf's GCN repository:
https://github.com/tkipf/gcn/tree/master/gcn/data
Thanks,
Petar
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Thanks
from dgi.
I mean how are the files in these datasets made?
@PetarV-
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Perhaps this description can help?
https://github.com/kimiyoung/planetoid/blob/master/README.md
I'm sorry I cannot be of much more help than that---I didn't take part in preparing the files.
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Ok, thank you for your answer.
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Hi Petar,
Can you provide Reddit and PPI datasets in the format used in the code?
Thanks
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Hello,
For PPI, the preprocessing code found in:
https://github.com/PetarV-/GAT/blob/master/utils/process_ppi.py
should be enough to get you started.
For Reddit, we were unable to get the PyTorch version of GraphSAGE to cooperate, and thus we used the TensorFlow version:
https://github.com/williamleif/GraphSAGE
as a starting point, and modified it to support DGI and load Reddit. Currently there are no plans to release this modified codebase.
Thanks,
Petar
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Thanks a lot!
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Related Issues (19)
- Help! HOT 4
- objective function in the paper?
- Script for inductive training HOT 2
- Why do we need to calculate for expectation before sum
- graph
- DATA
- Could anybody explain what are x,tx,allx,y,ty,ally? HOT 1
- About the meaning of learned features HOT 2
- If I want to add features for my edges, can I simply replace the encoder network with a network that supports edge_attr?
- Mean accuracy on fixed representation HOT 2
- Codes on reddit dataset HOT 1
- The code for Reddit!HELP! HOT 1
- Out of Memory on Pubmed Dataset HOT 6
- Corruption function only on node features X not graph structure A?
- Question about PPI dataset
- sigmoid function is missing in layers/discriminator.py HOT 1
- The time cost on Reddit HOT 2
- Error in AvgReadout
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