Making Classic GNNs Strong Baselines Across Varying Homophily: A Smoothness-Generalization Perspective

Ming Gu, Zhuonan Zheng, Sheng Zhou +5

Graph Neural Networks (GNNs) have achieved great success but are often considered to be challenged by varying levels of homophily in graphs. Recent \textit{empirical} studies have…