Local pooling layers coarsen the graph via downsampling. We present hereSubsequently, several learnable local pooling strategies that have been proposed are presented.<ref name=lui2022 /> For each case, the input is the initial graph is represented by a matrix <math>\mathbf{X}</math> of node features, and the graph adjacency matrix <math>\mathbf{A}</math>. The output is the new matrix <math>\mathbf{X}'</math>of node features, and the new graph adjacency matrix <math>\mathbf{A}'</math>.
