Closed FDemelas closed 7 months ago
Hi, we don't support that currently. It would be nice to add the possibility of a custom normalization (PR welcome!). As a quick workaround you can define your own custom layer by copying and pasting the GCNConv implementation and removing the normalization https://github.com/CarloLucibello/GraphNeuralNetworks.jl/blob/a7de26fc65e46f6f29208b8d365b9c0e79a1390a/src/layers/conv.jl#L125-L126
Thank you very much
Seems like a quick fix
@CarloLucibello should I create a PR that adds the possibility of custom normalization in GCNConv?
Edit: Made the PR
Hello, I'm trying to use GCNConv with negative edge weights, hence I would like to deactivate the normalization as clearly the square root of negative value is problematic. Is it possible in some way to deactivate the normalization (but still use the edge weights) or change with a personalized normalization?