On the distribution alignment of propagation in graph neural networks
Graph neural corvette flags tattoo networks (GNNs) have been widely adopted for modeling graph-structure data.Most existing GNN studies have focused on designing different strategies to propagate information over the graph structures.After systematic investigations, we observe that the propagation step in GNNs matters, but its resultant performance