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📄 Abstract
Abstract: Probabilities of causation provide principled ways to assess causal
relationships but face computational challenges due to partial identifiability
and latent confounding. This paper introduces both algorithmic simplifications,
significantly reducing the computational complexity of calculating tighter
bounds for these probabilities, and a novel methodological framework for Root
Cause Analysis that systematically employs these causal metrics to rank entire
causal paths.