The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory

dc.contributor.author	Otte, Sebastian
dc.date.accessioned	2023-12-22T11:56:01Z
dc.date.available	2023-12-22T11:56:01Z
dc.date.issued	2023-09
dc.identifier.issn	0893-6080
dc.identifier.uri	http://hdl.handle.net/10900/148843
dc.language.iso	en	de_DE
dc.publisher	Elsevier	de_DE
dc.relation.uri	http://dx.doi.org/10.1016/j.neunet.2023.06.036	de_DE
dc.subject.ddc	004	de_DE
dc.subject.ddc	570	de_DE
dc.subject.ddc	610	de_DE
dc.title	The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory	de_DE
dc.type	Article	de_DE
utue.quellen.id	20230928000000_00097
utue.publikation.seiten	85-104	de_DE
utue.personen.roh	Oladyshkin, Sergey
utue.personen.roh	Praditia, Timothy
utue.personen.roh	Kroeker, Ilja
utue.personen.roh	Mohammadi, Farid
utue.personen.roh	Nowak, Wolfgang
utue.personen.roh	Otte, Sebastian
dcterms.isPartOf.ZSTitelID	Neural Networks	de_DE
dcterms.isPartOf.ZS-Volume	166	de_DE
utue.fakultaet	07 Mathematisch-Naturwissenschaftliche Fakultät	de_DE