Mixed-curvature Variational Autoencoders
dc.contributor.author
Skopek, Ondrej
dc.contributor.supervisor
Hofmann, Thomas
dc.contributor.supervisor
Ganea, Octavian-Eugen
dc.contributor.supervisor
Bécigneul, Gary
dc.date.accessioned
2019-10-24T09:21:58Z
dc.date.available
2019-10-23T13:14:27Z
dc.date.available
2019-10-24T09:21:58Z
dc.date.issued
2019
dc.identifier.uri
http://hdl.handle.net/20.500.11850/372387
dc.identifier.doi
10.3929/ethz-b-000372387
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
ETH Zurich
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.title
Mixed-curvature Variational Autoencoders
en_US
dc.type
Master Thesis
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2019-10-24
ethz.size
144 p.
en_US
ethz.publication.place
Zurich
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02661 - Institut für Maschinelles Lernen / Institute for Machine Learning::09462 - Hofmann, Thomas / Hofmann, Thomas
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02661 - Institut für Maschinelles Lernen / Institute for Machine Learning::09462 - Hofmann, Thomas / Hofmann, Thomas
en_US
ethz.date.deposited
2019-10-23T13:14:38Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2020-02-15T22:10:38Z
ethz.rosetta.lastUpdated
2020-12-02T16:14:01Z
ethz.rosetta.versionExported
true
ethz.COinS
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Publication type
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Master Thesis [2010]