readout layer

A readout layer is an additional layer added to a GNN to achieve the desired output type/dimension for graph-level tasks or other learning tasks on graphs that require an output that is not a graph signal.

In node-level tasks (ex source localization, community detection, citation networks, etc), both the input and the output are graph signals $x\in {\mathbb{R}}^{n\times d_0},y\in {\mathbb{R}}^{n\times d_L}$. Thus, the map ${\mathrm{\Phi }}_H$ is composed strictly of GNN layers.

• Benefit: convolutional graph filters are local. This ensures a parameterization that is independent of graph size $n$