In deep neural networks, many researchers have noticed that the optimal depth is often very shallow due to the over-smoothing issue, i.e., nodes in deeper layers tend to have similar representations. To solve this issue, residue connection has been proposed and it allows deeper layers to attend to much shallower previous layers directly. This idea can be applied to GCN, such as in the GCN model proposed by Kipf and Welling, residue connection is used to allow for a deeper network.