Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-566
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dc.contributor.authorGerber, Susanne-
dc.contributor.authorOlsson, Simon-
dc.contributor.authorNoé, Frank-
dc.contributor.authorHorenko, Illia-
dc.date.accessioned2018-03-22T10:34:59Z-
dc.date.available2018-03-22T11:34:59Z-
dc.date.issued2018-
dc.identifier.urihttps://openscience.ub.uni-mainz.de/handle/20.500.12030/568-
dc.description.sponsorshipDFG, Open Access-Publizieren Universität Mainz / Universitätsmedizin-
dc.language.isoeng-
dc.rightsCC BYde_DE
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subject.ddc510 Mathematikde_DE
dc.subject.ddc510 Mathematicsen_GB
dc.titleA scalable approach to the computation of invariant measures for high-dimensional Markovian systemsen_GB
dc.typeZeitschriftenaufsatzde_DE
dc.identifier.doihttp://doi.org/10.25358/openscience-566-
jgu.type.dinitypearticle-
jgu.type.versionPublished versionen_GB
jgu.type.resourceText-
jgu.organisation.departmentFB 10 Biologie-
jgu.organisation.number7970-
jgu.organisation.nameJohannes Gutenberg-Universität Mainz-
jgu.rights.accessrightsopenAccess-
jgu.journal.titleScientific reports-
jgu.journal.volume8-
jgu.pages.alternativeArt. 1796-
jgu.publisher.year2018-
jgu.publisher.nameMacmillan Publishers Limited, part of Springer Nature-
jgu.publisher.placeLondon-
jgu.publisher.urihttp://dx.doi.org/10.1038/s41598-018-19863-4-
jgu.publisher.issn2045-2322-
jgu.organisation.placeMainz-
jgu.subject.ddccode510-
opus.date.accessioned2018-03-22T10:34:59Z-
opus.date.modified2018-03-22T10:53:27Z-
opus.date.available2018-03-22T11:34:59-
opus.subject.dfgcode00-000-
opus.organisation.stringFB 10: Biologie: Institut für Entwicklungsbiologie und Neurobiologiede_DE
opus.identifier.opusid58018-
opus.institute.number1012-
opus.metadataonlyfalse-
opus.type.contenttypeKeinede_DE
opus.type.contenttypeNoneen_GB
opus.affiliatedGerber, Susanne-
jgu.publisher.doi10.1038/s41598-018-19863-4
Appears in collections:JGU-Publikationen

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