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dc.date.accessioned2022-08-17T16:08:34Z
dc.date.available2022-08-17T16:08:34Z
dc.date.created2022-08-16T14:21:52Z
dc.date.issued2022
dc.identifier.citationLohrmann, Timo Kvellestad, Anders De Bin, Riccardo . A modified dividing local Gaussian processes algorithm for theoretical particle physics applications. Proceedings of the 36th International Workshop on Statistical Modelling. 2022, 222-227 EUT Edizioni Università di Trieste
dc.identifier.urihttp://hdl.handle.net/10852/95054
dc.description.abstractWe explore the use of dividing local Gaussian processes in the context of theoretical particle physics. We adapt an existing algorithm to the specific problem, trading some speed for a better precision. An intensive sensitivity analysis is performed.
dc.languageEN
dc.publisherEUT Edizioni Università di Trieste
dc.titleA modified dividing local Gaussian processes algorithm for theoretical particle physics applications
dc.title.alternativeENEngelskEnglishA modified dividing local Gaussian processes algorithm for theoretical particle physics applications
dc.typeChapter
dc.creator.authorLohrmann, Timo
dc.creator.authorKvellestad, Anders
dc.creator.authorDe Bin, Riccardo
cristin.unitcode185,15,13,25
cristin.unitnameStatistikk og Data Science
cristin.ispublishedtrue
cristin.fulltextoriginal
dc.identifier.cristin2043490
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.btitle=Proceedings of the 36th International Workshop on Statistical Modelling&rft.spage=222&rft.date=2022
dc.identifier.startpage222
dc.identifier.endpage227
dc.identifier.pagecount629
dc.identifier.urnURN:NBN:no-97577
dc.type.documentBokkapittel
dc.type.peerreviewedPeer reviewed
dc.source.isbn978-88-5511-309-0
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/95054/5/Lohrmann-Kvellestad-DeBin.pdf
dc.type.versionPublishedVersion
cristin.btitleProceedings of the 36th International Workshop on Statistical Modelling


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