Design and analysis of spectral graph neural networks : adaptive filtering, local topology, and generalization

Spectral Graph Neural Networks (GNNs) operate by filtering graph signals in the frequency domain. While highly successful, standard spectral models rely on global, low-degree polynomial filters. This design choice introduces three main limitations: it restricts spectral adaptivity on complex topolog