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Low-Rank Projections of GCNs Laplacian
release_nqdldv3ag5fjtmgmd6mpbn4c64
by
Nathan Grinsztajn
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as a article
.
2021
Abstract
In this work, we study the behavior of standard models for community
detection under spectral manipulations. Through various ablation experiments,
we evaluate the impact of bandpass filtering on the performance of a GCN: we
empirically show that most of the necessary and used information for nodes
classification is contained in the low-frequency domain, and thus contrary to
images, high frequencies are less crucial to community detection. In
particular, it is sometimes possible to obtain accuracies at a state-of-the-art
level with simple classifiers that rely only on a few low frequencies.
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2106.07360v1
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