Fig. 1.

A comparison between the traditional readout and the convolutional readout. Panel A shows how a typical readout layer works and panel B shows how a convolutional readout works. The number of nodes is denoted by n. Both m and $1(l<=m)$ denote the dimension of node features in each layer separately. In our model, n equals m and equals l.