Record link: 
http://hdl.handle.net/20.500.12708/223781
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Title: 
Towards Certification of Uncertainty Calibration under AdversarialAttacks
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Citation: 
Emde, C., Pinto, F., Lukasiewicz, T., Torr, P., & Bibi, A. (2025). Towards Certification of Uncertainty Calibration under AdversarialAttacks. In The Thirteenth International Conference on Learning Representations,{ICLR} 2025, Singapore, April 24-28, 2025. Thirteenth International Conference on Learning Representations (ICLR 2025), Singapore.
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Emde, Cornelius 
Pinto, Francesco 
Lukasiewicz, Thomas 
Torr, Philip 
Bibi, Adel 
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Organisational Unit: 
E192-07 - Forschungsbereich Artificial Intelligence Techniques 
E192-03 - Forschungsbereich Knowledge Based Systems 
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Published in: 
The Thirteenth International Conference on Learning Representations,{ICLR} 2025, Singapore, April 24-28, 2025 
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Date (published): 
2025
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Event name: 
Thirteenth International Conference on Learning Representations (ICLR 2025) 
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Event date: 
24-Apr-2025 - 28-Apr-2025
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Event place: 
Singapore
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Number of Pages: 
41
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Peer reviewed: 
Yes
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Keywords: 
machine learning; Adversarial Robustness; Certification; Adversarial Training; Uncertainty Quantification; Calibration; Deep Learning; Certified Calibration
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Research Areas: 
Information Systems Engineering: 100%
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Science Branch: 
1020 - Informatik: 80%
1010 - Mathematik: 20%
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Appears in Collections:
Conference Paper

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