Search Results for author: Thomas Doms

Found 2 papers, 0 papers with code

Functional trustworthiness of AI systems by statistically valid testing

no code implementations4 Oct 2023 Bernhard Nessler, Thomas Doms, Sepp Hochreiter

The authors are concerned about the safety, health, and rights of the European citizens due to inadequate measures and procedures required by the current draft of the EU Artificial Intelligence (AI) Act for the conformity assessment of AI systems.

valid

Trusted Artificial Intelligence: Towards Certification of Machine Learning Applications

no code implementations31 Mar 2021 Philip Matthias Winter, Sebastian Eder, Johannes Weissenböck, Christoph Schwald, Thomas Doms, Tom Vogt, Sepp Hochreiter, Bernhard Nessler

Artificial Intelligence is one of the fastest growing technologies of the 21st century and accompanies us in our daily lives when interacting with technical applications.

BIG-bench Machine Learning Ethics

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