Experimental results obtained with the MinCutPool layer as presented in the 2020 ICML paper "Spectral Clustering with Graph Neural Networks for Graph Pooling"
Home Page: https://arxiv.org/abs/1907.00481
License: MIT License
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Hi, @FilippoMB @danielegrattarola , I have several questions w.r.t Equation (6).
? if it is normalized in the same way as the adjacency matrix, it is thus an Identity matrix, isn't it?Thank you very much in advance.
Thanks for your great job, how could i use clustering,py on my data?
I do not modify the code in Graph_Classification.py. When I run Graph_Classification.py, bug is as follow:
Traceback (most recent call last):
File "D:\Program Files\JetBrains\PyCharm 2019.3.3\plugins\python\helpers\pydev\pydevd.py", line 1448, in _exec
pydev_imports.execfile(file, globals, locals) # execute the script
File "D:\Program Files\JetBrains\PyCharm 2019.3.3\plugins\python\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "C:/Users/YZY1037/Desktop/Spectral-Clustering-with-Graph-Neural-Networks-for-Graph-Pooling-master/Graph_Classification.py", line 105, in <module>
A, X, y = get_graph_kernel_dataset(P['dataset_ID'], feat_norm='ohe')
File "C:\Users\YZY1037\Desktop\Spectral-Clustering-with-Graph-Neural-Networks-for-Graph-Pooling-master\utils\dataset_loader.py", line 90, in get_graph_kernel_dataset
nx_graphs, y = read_graphs_txt(dataset_ID)
File "C:\Users\YZY1037\Desktop\Spectral-Clustering-with-Graph-Neural-Networks-for-Graph-Pooling-master\utils\dataset_loader.py", line 67, in read_graphs_txt
g.node[n]['label'] = node_labels[i]
AttributeError: 'Graph' object has no attribute 'node'
I want to know why and how to solve it. Thanks.
Dear authors,
Thank you so much for making this work public!
I've been trying to reproduce the graph signal reconstruction results from your paper using the same ring and grid dataset you generated. For the graph u-net, using the built-in model in pyg (torch_geometric.nn.GraphUNet), I was getting results that look better than what you reported in the paper. The code and the result I obtained can be found here (https://drive.google.com/drive/folders/1WXe18TUM0J9dPQOHP8PVkWFcrF41sisV?usp=sharing)
If you do not have time to check the code, would you mind sharing the code you used to reconstruct graph signals for topKPooling? I can cross-check if I messed up with something.
Thank you so much for your attention.
Best regards,
Fuli
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