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dc.contributor.authorYeo, Kyongmin
dc.contributor.authorGrullon, Dylan EC
dc.contributor.authorSun, Fan-Keng
dc.contributor.authorBoning, Duane S
dc.contributor.authorKalagnanam, Jayant R
dc.date.accessioned2022-06-06T15:32:59Z
dc.date.available2022-06-06T15:32:59Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/1721.1/142888
dc.language.isoen
dc.publisherSociety for Industrial & Applied Mathematics (SIAM)en_US
dc.relation.isversionof10.1137/20M1323151en_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.sourceSIAMen_US
dc.titleVariational Inference Formulation for a Model-Free Simulation of a Dynamical System with Unknown Parameters by a Recurrent Neural Networken_US
dc.typeArticleen_US
dc.identifier.citationYeo, Kyongmin, Grullon, Dylan EC, Sun, Fan-Keng, Boning, Duane S and Kalagnanam, Jayant R. 2021. "Variational Inference Formulation for a Model-Free Simulation of a Dynamical System with Unknown Parameters by a Recurrent Neural Network." SIAM Journal on Scientific Computing, 43 (2).
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratory
dc.contributor.departmentSloan School of Management
dc.contributor.departmentMassachusetts Institute of Technology. Department of Physics
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.date.updated2022-06-06T15:18:15Z
dspace.orderedauthorsYeo, K; Grullon, DEC; Sun, F-K; Boning, DS; Kalagnanam, JRen_US
dspace.date.submission2022-06-06T15:18:16Z
mit.journal.volume43en_US
mit.journal.issue2en_US
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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