Gaussian Process Regression under Location Uncertainty using Monte Carlo Approximation

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but.event.date25.04.2023cs
but.event.titleSTUDENT EEICT 2023cs
dc.contributor.authorPtáček, Martin
dc.date.accessioned2023-07-17T05:57:35Z
dc.date.available2023-07-17T05:57:35Z
dc.date.issued2023cs
dc.description.abstractGaussian Process Regression (GPR) is a commonstatistical framework for spatial function estimation. While itsflexibility and availability of closed-form estimation solutionafter training are its advantages, it suffers on applicabilityconstraints in scenarios with uncertain training positions. Thispaper presents the derivation of the exact GPR operating onuncertain training positions along with approximation of theresulting terms using Monte Carlo (MC) sampling. This methodis then implemented in a simulation environment and shown toimprove the estimation quality over the standard GPR approachwith uncertain training positions.en
dc.formattextcs
dc.format.extent222-226cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings II of the 29st Conference STUDENT EEICT 2023: Selected papers. s. 222-226. ISBN 978-80-214-6154-3cs
dc.identifier.doi10.13164/eeict.2023.222
dc.identifier.isbn978-80-214-6154-3
dc.identifier.issn2788-1334
dc.identifier.urihttp://hdl.handle.net/11012/210695
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings II of the 29st Conference STUDENT EEICT 2023: Selected papersen
dc.relation.urihttps://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_2_v2.pdfcs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectSpatial function estimationen
dc.subjectGPRen
dc.subjectUncertaintraining positionsen
dc.subjectProbabilistic inferenceen
dc.subjectMonte Carlo approximationen
dc.titleGaussian Process Regression under Location Uncertainty using Monte Carlo Approximationen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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