2026
Full-Spectrum Graph Neural Network: Expressive and Scalable
ICML 2026poster
It is well established that spectral graph neural networks (GNNs) can universally approximate node signals; however, their expressive power remains bounded by the 1-dimensional Weisfeiler–Lehman test, which is mirrored in their lack of universality for higher-order signals. To go beyond this bound, …