Jan. 20, 2022, 2:11 a.m. | Yimeng Min, Frederik Wenkel, Guy Wolf

cs.LG updates on arXiv.org arxiv.org

Geometric scattering has recently gained recognition in graph representation
learning, and recent work has shown that integrating scattering features in
graph convolution networks (GCNs) can alleviate the typical oversmoothing of
features in node representation learning. However, scattering often relies on
handcrafted design, requiring careful selection of frequency bands via a
cascade of wavelet transforms, as well as an effective weight sharing scheme to
combine low- and band-pass information. Here, we introduce a new
attention-based architecture to produce adaptive task-driven node …

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