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Mathematics, Statistics, and Geometry of Extreme Events in High Dimensions

dc.date.accessioned2025-05-21T08:48:58Z
dc.date.available2025-05-21T08:48:58Z
dc.date.issued2024
dc.identifier.urihttp://publications.mfo.de/handle/mfo/4252
dc.description.abstractThe workshop brought together researchers contributing to various recent topics in Extreme Value Theory. Discussions and talks included recent probabilistic development in the theory of regular variation, advances in multivariate representations compatible with sparsity structures, statistical inference in both high dimensional and time series frameworks, and novel applications and emerging directions that leverage recent advances in deep learning.
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/*
dc.titleMathematics, Statistics, and Geometry of Extreme Events in High Dimensions
dc.rights.licenseUnless otherwise noted, the content of this report is licensed under Creative Commons Attribution-ShareAlike 4.0 International.*
dc.identifier.doi10.14760/OWR-2024-38
local.series.idOWR-2024-38
local.subject.msc62
local.subject.msc60
local.subject.msc06
local.date-range18 Aug - 23 Aug 2024
local.workshopcode2434
local.workshoptitleMathematics, Statistics, and Geometry of Extreme Events in High Dimensions
local.organizersRichard Davis, New York; Rafal Kulik, Ottawa; Anne Sabourin, Palaiseau; Stilian Stoev, Ann Arbor
local.report-nameWorkshop Report 2024,38
local.opc-photo-id2434
local.publishers-doi10.4171/OWR/2024/38


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