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Simple Multigraph Convolution Networks
March 11, 2024, 4:41 a.m. | Danyang Wu, Xinjie Shen, Jitao Lu, Jin Xu, Feiping Nie
cs.LG updates on arXiv.org arxiv.org
Abstract: Existing multigraph convolution methods either ignore the cross-view interaction among multiple graphs, or induce extremely high computational cost due to standard cross-view polynomial operators. To alleviate this problem, this paper proposes a Simple MultiGraph Convolution Networks (SMGCN) which first extracts consistent cross-view topology from multigraphs including edge-level and subgraph-level topology, then performs polynomial expansion based on raw multigraphs and consistent topologies. In theory, SMGCN utilizes the consistent topologies in polynomial expansion rather than standard cross-view …
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