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Physics-Informed Neural Networks with Hard Constraints for Inverse Design

dc.contributor.authorLu, Lu
dc.contributor.authorPestourie, Raphaël
dc.contributor.authorYao, Wenjie
dc.contributor.authorWang, Zhicheng
dc.contributor.authorVerdugo, Francesc
dc.contributor.authorJohnson, Steven G.
dc.date.accessioned2021-12-13T12:50:40Z
dc.date.available2021-12-13T12:50:40Z
dc.date.issued2021-01
dc.identifier.issn1064-8275
dc.identifier.issn1095-7197
dc.identifier.urihttps://hdl.handle.net/1721.1/138438
dc.publisherSociety for Industrial & Applied Mathematics (SIAM)en_US
dc.relation.isversionof10.1137/21m1397908en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceRaphael Pestourieen_US
dc.subjectApplied Mathematicsen_US
dc.subjectComputational Mathematicsen_US
dc.titlePhysics-Informed Neural Networks with Hard Constraints for Inverse Designen_US
dc.typeArticleen_US
dc.identifier.citationLu, Lu, Pestourie, Raphaël, Yao, Wenjie, Wang, Zhicheng, Verdugo, Francesc et al. 2021. "Physics-Informed Neural Networks with Hard Constraints for Inverse Design." SIAM Journal on Scientific Computing, 43 (6).
dc.relation.journalSIAM Journal on Scientific Computingen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.identifier.doi10.1137/21M1397908
dspace.date.submission2021-12-11T04:55:58Z
mit.journal.volume43en_US
mit.journal.issue6en_US
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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