Open DongXiang-CV opened 3 years ago
Thanks a lot. I have another question about the Figure 1. Semi-supervised node classification accuracy v.s. degree.
In the main body of the paper, you group the nodes of each graph according to their degrees. The i-th group consists of nodes with degrees in the range [2^i, 2^{i+1}). The x-axis 10^{1}, 10^{2}, 10^{3} in your figure denote index $i$ right?
The x-axis 10^{1}, 10^{2}, 10^{3} denote degrees. We don't show the value of $i$ in the figure. The eight points on each line are 2^{1}, 2^{2}, ..., 2^{8}.
Thanks for your reply.
I have some questions on Figure 1. Semi-supervised node classification accuracy v.s. degree.
Do you plot the accuracy on the test nodes or all nodes?
From your Table 3. the 64-layer GCN, the test accuracy is already 28.7. However, from your Figure 1, the accuracy is far from 20. The 16-layer and 8-layer GCN also have the same problem. Can you tell me why this happens. Do I missing something?
It would be better if you can share the GCN code for plotting your Figure 1
Thank you very much
The data split in Figure 1 is different from that in table 3. In Figure 1, we randomly select about 100 nodes for training and plot the figure on other nodes. The code will be released soon.
Hi authors,
Could you please provide the implementations of deeper baselines such as JKNet (64) and Incep (64) ?
Thank you very much!