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Hi! This one is not an issue but I would appreciate if you gave your two cents.
In the "Localized Polynomial Filters" section of your paper you mention that we can build convolutional layers using the orthonormal basis in the Krylov subspace. Have you tried to implement this method? If so, can you share some results?
I did my own implementation - however I find that Chebyshev approximation performs significantly better in the standard classification tasks (cora, citeseer, pubmed). I hope you can confirm this. Propagation through the Lanczos algorithm is not that demanding though, it works fine for larger graphs.
Thank you for any help you can provide!
The text was updated successfully, but these errors were encountered:
Hi! This one is not an issue but I would appreciate if you gave your two cents.
In the "Localized Polynomial Filters" section of your paper you mention that we can build convolutional layers using the orthonormal basis in the Krylov subspace. Have you tried to implement this method? If so, can you share some results?
I did my own implementation - however I find that Chebyshev approximation performs significantly better in the standard classification tasks (cora, citeseer, pubmed). I hope you can confirm this. Propagation through the Lanczos algorithm is not that demanding though, it works fine for larger graphs.
Thank you for any help you can provide!
The text was updated successfully, but these errors were encountered: