2 papers
cs.LG2024
A practical approach to evaluating the adversarial distance for machine learning classifiers
Georg Siedel, Ekagra Gupta, Andrey Morozov
Robustness is critical for machine learning (ML) classifiers to ensure consistent performance in real-world applications where models may encounter corrupted or adversarial inputs.…
cs.RO2024
Concept: Dynamic Risk Assessment for AI-Controlled Robotic Systems
Philipp Grimmeisen, Friedrich Sautter, Andrey Morozov
AI-controlled robotic systems pose a risk to human workers and the environment. Classical risk assessment methods cannot adequately describe such black box systems. Therefore, new…