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()

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.

ChebNet dataset

I saw the code has this code sentence

how can i get this datasets folder