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License: GNU General Public License v3.0
Second-Order Pooling for Graph Neural Networks
License: GNU General Public License v3.0
Hello, thank you for the code.
I was wondering if you could send me the link to the reference paper of this work please?
I was not able to find it.
Hi,I'm now trying to reproduce the results of your paper.
I tried to adjust hidden_ Dim(16,32,64) and batch_size,(32,128)) .However, in many datasets (such as PTC), there is a certain gap between the my results and this paper. I also try to adjust the random seed, but the results are still not improved.
Do I need to adjust the parameters (lr, layer_num) which hava been given in the paper to achieve the results of the paper?
look forward to your answer
Thanks for the code.
I use pytorch-geometric to rewrite your model. I use the same hyperparameters as yours, but I cann't reproduce your method.
In your code, you use the max test acc as the final result. In fact, many existing method use the val set to choose the bese epoch for test set. Many baselines in your paper do like it. So, I think this is a little unfair. Because of this , your results are in the level I can not reach.
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