Distribution Preserving Graph Representation Learning
Distribution Preserving Graph Representation Learning
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Graph neural network (GNN) is effective to model graphs for distributed representations of nodes and an entire graph. Recently, research on the expressive power of GNN attracted growing attention. A highly-expressive GNN has the ability to generate discriminative graph representations. However, in the end-to-end training process for a certain graph...
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Distribution Preserving Graph Representation Learning
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TN_cdi_proquest_journals_2634667278
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2634667278
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E-ISSN
2331-8422