3 papers
cs.LG2026
A Framework for Directed Hypergraph Signal Processing via tensor t-SVD
Carlos Mundo-Levano, Nicolás Bello, Daniel L. Lau +1
We introduce Directed Hypergraph Signal Processing (DHGSP), a unified framework that extends graph signal processing to accommodate both higher-order (polyadic) and asymmetric (dir…
cs.LG2025
Scalable Hypergraph Structure Learning with Diverse Smoothness Priors
Benjamin T. Brown, Haoxiang Zhang, Daniel L. Lau +1
In graph signal processing, learning the weighted connections between nodes from a set of sample signals is a fundamental task when the underlying relationships are not known a pri…
cs.LG2025
Generalization Performance of Hypergraph Neural Networks
Yifan Wang, Gonzalo R. Arce, Guangmo Tong
Hypergraph neural networks have been promising tools for handling learning tasks involving higher-order data, with notable applications in web graphs, such as modeling multi-way hy…