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How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review.

, , , , , , , , , и . CoRR, (2021)

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Florian Klasovsky

Syntheseparameter-Reaktivitätsbeziehungen für neue Palladiumoxidkatalysatoren in feinchemischen Hydrierungen. TU Darmstadt, (2009)

Florian Franz

Realzeittest von Fahrzeugsoftware-Komponenten. TU München, (2009)

Florian Exl

Einflussfaktoren auf die Bewertung der Hydrophobieeigenschaften von Isolierwerkstoffen. TU München, (2010)

Florian Beißner

Funktionelle Bildgebung des vegetativen Nervensystems: neue Ansätze zur fMRT-Messung des menschlichen Hirnstamms. Uni Frankfurt Main, (2010)

Florian Engelhardt

Börsenprospekthaftung der Leitungsorgane von Emittenten in Deutschland und Schweden. TU Dresden, (2007)
 

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Common challenges of deep reinforcement learning applications development: an empirical study., , , , и . Empir. Softw. Eng., 29 (4): 95 (июля 2024)A Probabilistic Framework for Mutation Testing in Deep Neural Networks., , и . CoRR, (2022)Common Challenges of Deep Reinforcement Learning Applications Development: An Empirical Study., , , , и . CoRR, (2023)How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review., , , , , , , , , и . CoRR, (2021)Bugs in Large Language Models Generated Code: An Empirical Study., , , , , и . CoRR, (2024)How to certify machine learning based safety-critical systems? A systematic literature review., , , , , , , , , и . Autom. Softw. Eng., 29 (2): 38 (2022)Chain of Targeted Verification Questions to Improve the Reliability of Code Generated by LLMs., , , и . AIware, ACM, (2024)Mutation Testing of Deep Reinforcement Learning Based on Real Faults., , , , и . ICST, стр. 188-198. IEEE, (2023)Deep Learning Model Reuse in the HuggingFace Community: Challenges, Benefit and Trends., , , , и . SANER, стр. 512-523. IEEE, (2024)