2023
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion
AISTATS 2023poster
Graph neural networks are widely used tools for graph prediction tasks. Motivated by their empirical performance, prior works have developed generalization bounds for graph neural networks, which scale with graph structures in terms of the maximum degree. In this paper, we present generalization bou…