Machine learning a manifold

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dc.contributor.author Craven, Sean
dc.contributor.author Croon, Djuna
dc.contributor.author Cutting, Daniel
dc.contributor.author Houtz, Rachel
dc.date.accessioned 2022-07-14T11:50:01Z
dc.date.available 2022-07-14T11:50:01Z
dc.date.issued 2022-05-25
dc.identifier.citation Craven , S , Croon , D , Cutting , D & Houtz , R 2022 , ' Machine learning a manifold ' , Physical Review D , vol. 105 , no. 9 , 096030 . https://doi.org/10.1103/PhysRevD.105.096030
dc.identifier.other PURE: 217234900
dc.identifier.other PURE UUID: 9382b78d-3ff5-4aee-92d5-ae8d24242d79
dc.identifier.other Bibtex: craven2021machine
dc.identifier.other WOS: 000810236400010
dc.identifier.other Scopus: 85131594949
dc.identifier.other ORCID: /0000-0002-7395-7802/work/108467228
dc.identifier.uri http://hdl.handle.net/10138/346187
dc.format.extent 6
dc.language.iso eng
dc.relation.ispartof Physical Review D
dc.rights cc_by
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject 114 Physical sciences
dc.subject SYMMETRY
dc.title Machine learning a manifold en
dc.type Article
dc.contributor.organization Particle Physics and Astrophysics
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.1103/PhysRevD.105.096030
dc.relation.issn 2470-0010
dc.rights.accesslevel openAccess
dc.type.version publishedVersion

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