Physics-inspired Machine Learning
dc.contributor.author
Rusch, Thorben Konstantin
dc.contributor.supervisor
Mishra, Siddhartha
dc.contributor.supervisor
Mahoney, Michael W.
dc.contributor.supervisor
Welling, Max
dc.date.accessioned
2023-10-19T06:00:39Z
dc.date.available
2023-10-18T12:40:50Z
dc.date.available
2023-10-19T05:55:03Z
dc.date.available
2023-10-19T06:00:39Z
dc.date.issued
2023
dc.identifier.uri
http://hdl.handle.net/20.500.11850/637340
dc.identifier.doi
10.3929/ethz-b-000637340
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
Physics-inspired Machine Learning
en_US
dc.type
Doctoral Thesis
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2023-10-19
ethz.size
185 p.
en_US
ethz.code.ddc
DDC - DDC::5 - Science::510 - Mathematics
en_US
ethz.identifier.diss
29544
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::02000 - Dep. Mathematik / Dep. of Mathematics::02501 - Seminar für Angewandte Mathematik / Seminar for Applied Mathematics::03851 - Mishra, Siddhartha / Mishra, Siddhartha
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02000 - Dep. Mathematik / Dep. of Mathematics::02501 - Seminar für Angewandte Mathematik / Seminar for Applied Mathematics::03851 - Mishra, Siddhartha / Mishra, Siddhartha
en_US
ethz.date.deposited
2023-10-18T12:40:50Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2023-10-19T05:55:05Z
ethz.rosetta.lastUpdated
2024-02-03T05:21:52Z
ethz.rosetta.versionExported
true
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Doctoral Thesis [30301]