2 papers
math.SP2024
Limiting Over-Smoothing and Over-Squashing of Graph Message Passing by Deep Scattering Transforms
Yuanhong Jiang, Dongmian Zou, Xiaoqun Zhang +1
Graph neural networks (GNNs) have become pivotal tools for processing graph-structured data, leveraging the message passing scheme as their core mechanism. However, traditional GNN…
cs.LG2024
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing
Keke Huang, Yu Guang Wang, Ming Li +1
Spectral Graph Neural Networks (GNNs), alternatively known as graph filters, have gained increasing prevalence for heterophily graphs. Optimal graph filters rely on Laplacian eigen…