Inductive Graph Few-shot Class Incremental Learning
Inductive Graph Few-shot Class Incremental Learning
About this item
Full title
Author / Creator
Li, Yayong , Moghadam, Peyman , Peng, Can , Ye, Nan and Koniusz, Piotr
Publisher
Ithaca: Cornell University Library, arXiv.org
Journal title
Language
English
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Publication information
Publisher
Ithaca: Cornell University Library, arXiv.org
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Scope and Contents
Contents
Node classification with Graph Neural Networks (GNN) under a fixed set of labels is well known in contrast to Graph Few-Shot Class Incremental Learning (GFSCIL), which involves learning a GNN classifier as graph nodes and classes growing over time sporadically. We introduce inductive GFSCIL that continually learns novel classes with newly emerging...
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Full title
Inductive Graph Few-shot Class Incremental Learning
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_proquest_journals_3127415970
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3127415970
Other Identifiers
E-ISSN
2331-8422
