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dc.contributor.authorLitvinenko, Alexander
dc.date.accessioned2018-04-22T06:54:17Z
dc.date.available2018-04-22T06:54:17Z
dc.date.issued2018-04-10
dc.identifier.urihttp://hdl.handle.net/10754/627579
dc.description.abstractUse H-matrices to approximate large covariance matrices in spatial statistics
dc.description.sponsorshipKAUST
dc.relation.isversionofhttp://hdl.handle.net/10754/626107
dc.subjecthierarchical matrices
dc.subjectParameter identification
dc.subjectHLIB
dc.subjectHLIBPro
dc.subjectMatern covariance
dc.titleLikelihood Approximation With Parallel Hierarchical Matrices For Large Spatial Datasets
dc.typePoster
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.conference.date8-12 April 2018
dc.conference.nameInverse Problems Workshop (UNQW04)
dc.conference.locationCambridge, USA
refterms.dateFOA2018-06-14T05:55:18Z


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