A Computationally Feasible Framework for Causal Probabilistic Explanation
Probabilistic Causal Impact (PCI) builds on actual causality and on Pearl's notions of probability of necessity and sufficiency, but recasts the question of explainability as an estimation problem on a probabilistic causal model that is easily approximated via Monte Carlo.
R. Urbaniak, Sam Witty, Daniel Waxman et al.
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