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

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