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Towards Expressive Graph Representation

Towards Expressive Graph Representation

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2450690280

Towards Expressive Graph Representation

About this item

Full title

Towards Expressive Graph Representation

Publisher

Ithaca: Cornell University Library, arXiv.org

Journal title

arXiv.org, 2020-10

Language

English

Formats

Publication information

Publisher

Ithaca: Cornell University Library, arXiv.org

More information

Scope and Contents

Contents

Graph Neural Network (GNN) aggregates the neighborhood of each node into the node embedding and shows its powerful capability for graph representation learning. However, most existing GNN variants aggregate the neighborhood information in a fixed non-injective fashion, which may map different graphs or nodes to the same embedding, reducing the mode...

Alternative Titles

Full title

Towards Expressive Graph Representation

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_2450690280

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2450690280

Other Identifiers

E-ISSN

2331-8422

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