A Friendly Introduction To Causality: Causality has been studied under several frameworks in statistics and artificial intelligence. We will briefly survey Pearl’s Structural Equation model and explain how interventions can be used to discover causality. We will also present a novel information theoretic framework for discovering causal directions from observational data when interventions are not possible. The starting point is conditional independence in joint probability distributions and no prior knowledge on causal inference is required.
Session Summary
A Friendly Introduction To Causality: Causality ha
MLconf 2016 San Francisco
Alex Dimakis
University of Texas at Austin
Associate Professor
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