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A generative modeling framework for statistical link analysis based on sparse data

Date

2018-01
Journal article
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dc.contributor.authorDe Ridder, Simon
dc.contributor.authorManfredi, Paolo
dc.contributor.authorDe Geest, Jan
dc.contributor.authorDeschrijver, Dirk
dc.contributor.authorDe Zutter, Daniel
dc.contributor.authorDhaene, Tom
dc.contributor.authorVande Ginste, Dries
dc.contributor.imecauthorDe Ridder, Simon
dc.contributor.imecauthorDeschrijver, Dirk
dc.contributor.imecauthorDe Zutter, Daniel
dc.contributor.imecauthorDhaene, Tom
dc.contributor.imecauthorVande Ginste, Dries
dc.contributor.orcidimecDeschrijver, Dirk::0000-0001-6600-1792
dc.contributor.orcidimecDhaene, Tom::0000-0003-2899-4636
dc.contributor.orcidimecVande Ginste, Dries::0000-0002-0178-288X
dc.date.accessioned2021-10-25T17:48:19Z
dc.date.available2021-10-25T17:48:19Z
dc.date.embargo9999-12-31
dc.date.issued2018-01
dc.identifier.issn2156-3950
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/30548
dc.identifier.urlhttp://ieeexplore.ieee.org/document/8107679/
dc.source.beginpage21
dc.source.endpage31
dc.source.issue1
dc.source.journalIEEE Transactions on Components, Packaging and Manufacturing Technology
dc.source.volume8
dc.title

A generative modeling framework for statistical link analysis based on sparse data

dc.typeJournal article
dspace.entity.typePublication
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