Dongrui Shen

High-Pass Matters: Theoretical Insights and Sheaflet-Based Design for Hypergraph Neural Networks

Hypergraph neural networks (HGNNs) have shown great potential in modeling higher-order relationships among multiple entities. However, most existing HGNNs primarily emphasize low-pass filtering while neglecting the role of high-frequency information. In this work, we present a theoretical investigat