Machine learning for scattering data: strategies, perspectives and applications to surface scattering

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dc.contributor.author Hinderhofer, Alexander
dc.contributor.author Greco, Alessandro
dc.contributor.author Starostin, Vladimir
dc.contributor.author Munteanu, Valentin
dc.contributor.author Pithan, Linus
dc.contributor.author Gerlach, Alexander
dc.contributor.author Schreiber, Frank
dc.date.accessioned 2023-08-17T12:26:47Z
dc.date.available 2023-08-17T12:26:47Z
dc.date.issued 2023
dc.identifier.issn 1600-5767
dc.identifier.uri http://hdl.handle.net/10900/144353
dc.language.iso en de_DE
dc.publisher Int Union Crystallography de_DE
dc.relation.uri http://dx.doi.org/10.1107/S1600576722011566 de_DE
dc.subject.ddc 540 de_DE
dc.subject.ddc 570 de_DE
dc.subject.ddc 610 de_DE
dc.title Machine learning for scattering data: strategies, perspectives and applications to surface scattering de_DE
dc.type Article de_DE
utue.quellen.id 20230619000000_01301
utue.publikation.seiten 3-11 de_DE
utue.personen.roh Hinderhofer, Alexander
utue.personen.roh Greco, Alessandro
utue.personen.roh Starostin, Vladimir
utue.personen.roh Munteanu, Valentin
utue.personen.roh Pithan, Linus
utue.personen.roh Gerlach, Alexander
utue.personen.roh Schreiber, Frank
dcterms.isPartOf.ZSTitelID Journal of Applied Crystallography de_DE
dcterms.isPartOf.ZS-Volume 56 de_DE
utue.fakultaet 07 Mathematisch-Naturwissenschaftliche Fakultät de_DE


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