dsgiitr/graph_nets

PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.

graph_nets's Issues

Question: GCN pytorch implementation

Thanks a lot for the code. Found it via your blog post about GCNs.

I see Kipf used Laplace symmetric normalisation - as you wrote also here: https://dsgiitr.com/blogs/gcn/

But I don't understand, why the diagonal degree matrix is produced using A instead of A_hat:

        self.A_hat = A+torch.eye(A.size(0))
        self.D     = torch.diag(torch.sum(A,1))  #<< should this not be self.A_hat?
        self.D     = self.D.inverse().sqrt()

ChebNet dataset

I saw the code has this code sentence

how can i get this datasets folder

Is unsupervised learning implemented for graphSage?

Is unsupervised learning implemented for graphSage?

Problems about graphsage

In GraphSage part, just one hop neighbors were used in enc1 and enc2.
Maybe , using 2 hop neighbors in enc1 and 1 hop neighbors in enc2 is more proper.
Just a little suggestion.