2021
Ego-GNNs: Exploiting Ego Structures in Graph Neural Networks
ICASSP 2021accepted
Graph neural networks (GNNs) have achieved remarkable success as a framework for deep learning on graph-structured data. However, GNNs are fundamentally limited by their tree-structured inductive bias: the WL-subtree kernel formulation bounds the representational capacity of GNNs, and polynomial-tim…