181 citations
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Showing 2026Show all
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cs.AI2026
CUBICS: Situation-aware performance estimation for safety-relevant ML components
Benjamin Herd, Jessica Kelly, Mario Trapp
Machine learning (ML) is a key technology driving innovation today, but ensuring ML safety remains a major challenge for safety-related applications. A promising idea is to build p…
stat.ME2026
Optimizing Experimental Design for Causal Effect Estimation with Partial Measurements
Leopold Mareis
Instrumental variable regression quantifies causal effects between a possibly confounded treatment variable and a response variable by leveraging an instrument $ X_…
cs.AI2026
A Subjective Logic-based method for runtime confidence updates in safety arguments
Benjamin Herd, Jessica Kelly, Clarissa Heinemann +1
We present a method for dynamic quantitative assurance that enhances static safety cases with continuous, runtime-driven confidence updates. The method quantifies and propagates co…