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dc.contributor.authorDiwale, Sanket
dc.contributor.authorEisner, Maximilian K
dc.contributor.authorCarpenter, Corinne
dc.contributor.authorSun, Weike
dc.contributor.authorRutledge, Gregory C
dc.contributor.authorBraatz, Richard D
dc.date.accessioned2022-05-16T16:42:53Z
dc.date.available2022-05-16T16:42:53Z
dc.date.issued2022-03-07
dc.identifier.urihttps://hdl.handle.net/1721.1/142548
dc.description.abstract<jats:p>An augmented Bayesian optimization approach is presented for materials discovery with noisy and unreliable measurements.</jats:p>en_US
dc.language.isoen
dc.publisherRoyal Society of Chemistry (RSC)en_US
dc.relation.isversionof10.1039/d1me00154jen_US
dc.rightsAttribution-NonCommercial-ShareAlike 4.0en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc/3.0/en_US
dc.sourceRoyal Society of Chemistryen_US
dc.titleBayesian optimization for material discovery processes with noiseen_US
dc.typeArticleen_US
dc.identifier.citationDiwale, Sanket, Eisner, Maximilian K, Carpenter, Corinne, Sun, Weike, Rutledge, Gregory C et al. 2022. "Bayesian optimization for material discovery processes with noise." Molecular Systems Design &amp; Engineering.
dc.relation.journalMolecular Systems Design &amp; Engineeringen_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.updated2022-05-16T16:35:20Z
dspace.orderedauthorsDiwale, S; Eisner, MK; Carpenter, C; Sun, W; Rutledge, GC; Braatz, RDen_US
dspace.date.submission2022-05-16T16:35:24Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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