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In this work, we study the behavior of standard models for communitydetection under spectral manipulations. Through various ablation experiments,we evaluate the impact of bandpass filtering on the performance of a GCN: weempirically show that most of the necessary and used information for nodesclassification is contained in the low-frequency domain, and thus contrary toimages, high frequencies are less crucial to community detection. Inparticular, it is sometimes possible to obtain accuracies at a state-of-the-artlevel with simple classifiers that rely only on a few low frequencies.

Low-Rank Projections of GCNs Laplacian