Graph Compression Networks

Guo, T

Zhu, X Wang, Y Chen, F

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2021 IEEE International Conference on Big Data (Big Data), 2021, pp. 1030-1036
Issue Date:: 2021-12-15

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Field	Value	Language
dc.contributor.author	Guo, T https://orcid.org/0000-0001-5130-3237
dc.contributor.author	Zhu, X
dc.contributor.author	Wang, Y
dc.contributor.author	Chen, F
dc.date	2021-12-15
dc.date.accessioned	2022-01-18T10:14:58Z
dc.date.available	2022-01-18T10:14:58Z
dc.date.issued	2021-12-15
dc.identifier.citation	2021 IEEE International Conference on Big Data (Big Data), 2021, pp. 1030-1036
dc.identifier.uri	http://hdl.handle.net/10453/153276
dc.language	en
dc.publisher	IEEE
dc.relation	iMOVE Australia Limited1-019
dc.relation.ispartof	2021 IEEE International Conference on Big Data (Big Data)
dc.relation.ispartof	2021 IEEE International Conference on Big Data (Big Data)
dc.relation.isbasedon	10.1109/bigdata52589.2021.9671652
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.title	Graph Compression Networks
dc.type	Conference Proceeding
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/A/DRsch The Data Science Institute
utslib.copyright.status	open_access	*
utslib.copyright.embargo	2024-01-31T00:00:00+1000Z
dc.date.updated	2022-01-18T10:14:57Z
pubs.finish-date	2021-12-18
pubs.publication-status	Published
pubs.start-date	2021-12-15

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