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Eine Ebene höherGruppiert nach: Dokumententyp |
Veröffentlichungsdatum
Springe zu: 2023
Anzahl der Publikationen: 2
2023
Sale, Yusuf; Caprio, Michele und Hüllermeier, Eyke 
ORCID: https://orcid.org/0000-0002-9944-4108
(August 2023):
Is the volume of a credal set a good measure for epistemic uncertainty?
Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI 2023), Pittsburgh, PA, USA, 1-3 August, 2023.
Evans, Robin J. und Shpitser, Ilya (Hrsg.):
In: Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence,
Bd. 216
PMLR. S. 1795-1804
[PDF, 1MB]
ORCID: https://orcid.org/0000-0002-9944-4108
(August 2023):
Is the volume of a credal set a good measure for epistemic uncertainty?
Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI 2023), Pittsburgh, PA, USA, 1-3 August, 2023.
Evans, Robin J. und Shpitser, Ilya (Hrsg.):
In: Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence,
Bd. 216
PMLR. S. 1795-1804
[PDF, 1MB]
Wimmer, Lisa; Sale, Yusuf; Hofman, Paul; Bischl, Bernd ORCID: https://orcid.org/0000-0001-6002-6980 und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(2023):
Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures?
Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI 2023), Pittsburgh, PA, USA, 1-3 August, 2023.
Evans, Robin J. und Shpitser, Ilya (Hrsg.):
In: Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence,
Bd. 216
PMLR. S. 2282-2292
[PDF, 1MB]
ORCID: https://orcid.org/0000-0001-6002-6980 und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(2023):
Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures?
Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI 2023), Pittsburgh, PA, USA, 1-3 August, 2023.
Evans, Robin J. und Shpitser, Ilya (Hrsg.):
In: Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence,
Bd. 216
PMLR. S. 2282-2292
[PDF, 1MB]