Interpretability of Learning Algorithms Encoded in Deep Neural Networks
dc.contributor.author
von Oswald, Johannes
dc.contributor.supervisor
Steger, Angelika
dc.contributor.supervisor
Sacramento, João
dc.contributor.supervisor
Pascanu, Razvan
dc.contributor.supervisor
Lajoie, Guillaume
dc.date.accessioned
2024-03-25T13:54:49Z
dc.date.available
2024-02-19T09:36:40Z
dc.date.available
2024-03-25T10:52:58Z
dc.date.available
2024-03-25T13:54:49Z
dc.date.issued
2024
dc.identifier.uri
http://hdl.handle.net/20.500.11850/660213
dc.identifier.doi
10.3929/ethz-b-000660213
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
Interpretability of Learning Algorithms Encoded in Deep Neural Networks
en_US
dc.type
Doctoral Thesis
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2024-03-25
ethz.size
156 p.
en_US
ethz.code.ddc
DDC - DDC::0 - Computer science, information & general works::004 - Data processing, computer science
en_US
ethz.identifier.diss
29862
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::02643 - Institut für Theoretische Informatik / Inst. Theoretical Computer Science::03672 - Steger, Angelika / Steger, Angelika
en_US
ethz.date.deposited
2024-02-19T09:36:40Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2024-03-25T13:54:50Z
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2024-03-25T13:54:50Z
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Publication type
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Doctoral Thesis [30301]