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dc.contributor.authorDanhaive, Renaud
dc.contributor.authorMueller, Caitlin T
dc.date.accessioned2022-09-26T14:20:45Z
dc.date.available2022-09-26T14:20:45Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/1721.1/145568
dc.language.isoen
dc.publisherElsevier BVen_US
dc.relation.isversionof10.1016/J.AUTCON.2021.103664en_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourceOther repositoryen_US
dc.titleDesign subspace learning: Structural design space exploration using performance-conditioned generative modelingen_US
dc.typeArticleen_US
dc.identifier.citationDanhaive, Renaud and Mueller, Caitlin T. 2021. "Design subspace learning: Structural design space exploration using performance-conditioned generative modeling." Automation in Construction, 127.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Architectureen_US
dc.relation.journalAutomation in Constructionen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2022-09-26T13:52:55Z
dspace.orderedauthorsDanhaive, R; Mueller, CTen_US
dspace.date.submission2022-09-26T13:53:10Z
mit.journal.volume127en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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