Convex--Concave Quadratic Spectral Filtering for Graph Neural Networks
arXiv:2606.24956v1 Announce Type: new Abstract: Spectral graph neural networks (GNNs) interpret message passing as frequency-selective filtering. While low-order spectral filters are efficient, their limited selectivity often leads to weak attenuation outside the passband, whereas high-order alternatives introduce optimization challenges. We propose DCQ-GNN, a spectral GNN based on a compact bank of adaptive convex--concave quadratic filters. By restricting the filter order to two while explicit...
arXiv cs.LG
·Ranhui Yan, Jia Cai, Mengzhu Chen, Haodong Yang
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