chandlerbang/simp-gcn

Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"

simp-gcn's Issues

some function is not defined

Hello I am a beginner. See the code address from your paper. There are some problems here：
In models_simp.py there GraphConvolution and GCFlatResBlock not defined
And in normalization.py

Can these problems be solved if I download deeprobust？

reproduce problem

Hello,I try to reproduce the result.Other datesets are ok,but there are two problems in reproducing Cora.

I searched some solutions about relative problems,but can't fix it.
So I ask for your help.Thank you.

How to use my own dataset.

I tried to use my own data but don't know the way.

About pubmed dataset result

I want to reproduce the result on the PubMed dataset with a 0.00 perturbation rate. However, I can't get the same results recorded in your paper while I just modify the ptb_rate to 0 in the .sh file. Does there need another hyperparameters setting since the providing .sh file corresponds to ptb_rate = 0.15?

Node embedding dimension

Argument 'hidden' controls the vector dimension of nodes? As you run the graph (adj matrix) through the gcn

The resulting size of the node vectors is the hidden value (128) or is it adjusted by the features as well?

Edge Weights in Adjacency Matrix

Would this code accommodate a graph with edge weights? Ideally I would want to use edge weights in the GCN adjacency matrix instead of '1's and '0's.

codes for Table 1

Hello, I would like to ask about the reproduce of Table 1. How do I reproduce the results? Generate the adjacency matrix and calculate the percentage by myself or am I missing something?

I have a question about the code

About ‘Adaptive Integration’，in which file in the code is this function implemented，‘model’ or ‘layer’？
And in which methods is it implemented？Please tell me ，and thank you for your answer.

Some questions about model_simp.py.

According to my understanding, in line 190-192 of model_simp.py:
" for i in range(len(self.midlayer)):
midgc = self.midlayer[i]
x = midgc(x, adj)"
"x" represents P^(l) in the paper, but I am confused about operation "midgc(x, adj)". Can you tell me which formula that "midgc(x, adj)" corresponds to in the paper?
Thanks!