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Michael Kläs
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Publications
- 2022
- [c26]Rasmus Adler, Michael Klaes:
Assurance Cases as Foundation Stone for Auditing AI-Enabled and Autonomous Systems: Workshop Results and Political Recommendations for Action from the ExamAI Project. HCI (45) 2022: 283-300 - [c25]Janek Groß, Rasmus Adler, Michael Kläs, Jan Reich, Lisa Jöckel, Roman Gansch:
Architectural Patterns for Handling Runtime Uncertainty of Data-Driven Models in Safety-Critical Perception. SAFECOMP 2022: 284-297 - [i14]Michael Kläs, Lisa Jöckel, Rasmus Adler, Jan Reich:
Integrating Testing and Operation-related Quantitative Evidences in Assurance Cases to Argue Safety of Data-Driven AI/ML Components. CoRR abs/2202.05313 (2022) - [i13]Janek Groß, Rasmus Adler, Michael Kläs, Jan Reich, Lisa Jöckel, Roman Gansch:
Architectural patterns for handling runtime uncertainty of data-driven models in safety-critical perception. CoRR abs/2206.06838 (2022) - [i12]Rasmus Adler, Michael Klaes:
Assurance Cases as Foundation Stone for Auditing AI-enabled and Autonomous Systems: Workshop Results and Political Recommendations for Action from the ExamAI Project. CoRR abs/2208.08198 (2022) - 2021
- [c24]Michael Kläs, Rasmus Adler, Ioannis Sorokos, Lisa Jöckel, Jan Reich:
Handling Uncertainties of Data-Driven Models in Compliance with Safety Constraints for Autonomous Behaviour. EDCC 2021: 95-102 - [c23]Michael Klaes, Rasmus Adler, Lisa Jöckel, Janek Groß, Jan Reich:
Using Complementary Risk Acceptance Criteria to Structure Assurance Cases for Safety-Critical AI Components. AISafety@IJCAI 2021 - 2019
- [i9]Rasmus Adler, Mohammed Naveed Akram, Pascal Bauer, Patrik Feth, Pascal Gerber, Andreas Jedlitschka, Lisa Jöckel, Michael Kläs, Daniel Schneider:
Hardening of Artificial Neural Networks for Use in Safety-Critical Applications - A Mapping Study. CoRR abs/1909.03036 (2019)
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