A comparative analysis of graph neural networks through similarity-based information propagation across diverse network structures
Abstract Information propagation over graph-structured data depends critically on the quality of node representations learned by graph neural networks (GNNs). However, how different GNN architectures organize embedding spaces and how these representations influence downstream propagation behavior remain insufficiently...