3 papers
eess.SP2026
Generalized Linear Graph Representation: A Compact Operator Space for Graph Signal Processing and Graph Neural Networks
Feiyue Zhao, Zhichao Zhang, Yangfan He
Graph Signal Processing (GSP) and Graph Neural Networks (GNNs) rely fundamentally on the matrix representation of the underlying graph topology. This representation defines key ope…
eess.SP2026
A Unified Fractional Spectral Framework for Spatiotemporal Graph Signals: Bi-Fractional Transform and Geodesic Coupling
Mingzhi Wang, Manjun Cui, Feiyue Zhao +2
Graph signal processing extends spectral analysis to data supported on irregular domains. Existing fractional transforms for two-dimensional graph signals, including the two-dimens…
cs.CV2025
Hierarchical Graph Feature Enhancement with Adaptive Frequency Modulation for Visual Recognition
Feiyue Zhao, Zhichao Zhang
Convolutional neural networks (CNNs) have demonstrated strong performance in visual recognition tasks, but their inherent reliance on regular grid structures limits their capacity…