Learning disentangled discrete representations

Friede, David; Reimers, Christian; Stuckenschmidt, Heiner; Niepert, Mathias

doi:10.1007/978-3-031-43421-1_35

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Learning disentangled discrete representations

Friede, D., Reimers, C., Stuckenschmidt, H., & Niepert, M. (2023). Learning disentangled discrete representations. In D. Koutra, C. Plant, R. M. Gomez, & E. Baralis (Eds.), Machine learning and knowledge discovery in databases: Research track. ECML PKDD 2023. Lecture Notes in Computer Science (pp. 593-609). Cham: Springer. doi:10.1007/978-3-031-43421-1_35.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-81A4-7 Version Permalink: https://hdl.handle.net/21.11116/0000-000D-F796-3

Genre: Conference Paper

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BGC4308.pdf (Publisher version), 2MB

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Creators:
Friede, David, Author
Reimers, Christian¹, Author
Stuckenschmidt, Heiner, Author
Niepert, Mathias, Author

Affiliations:
1Atmosphere-Biosphere Coupling, Climate and Causality, Dr. Alexander J. Winkler, Department Biogeochemical Integration, Prof. Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_3405368

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Dates: Accepted: 2023-07-26Published Online: 2023-09-18

Publication Status: Published online

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Rev. Type: No review

Identifiers: Other: BGC4308
DOI: 10.1007/978-3-031-43421-1_35

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Title: Machine learning and knowledge discovery in databases: Research track. ECML PKDD 2023. Lecture Notes in Computer Science

Source Genre: Book

Creator(s):
Koutra, D., Editor
Plant, C., Editor
Gomez, Rodriguez, M., Editor
Baralis, E., Editor
Bonchi, F., Author

Affiliations:
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Publ. Info: Cham : Springer

Pages: - Volume / Issue: 14172 Sequence Number: - Start / End Page: 593 - 609 Identifier: ISBN: 978-3-031-43420-4