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stat.ML2018
Enhancing Identification of Causal Effects by Pruning
Santtu Tikka, Juha Karvanen
Causal models communicate our assumptions about causes and effects in real-world phe- nomena. Often the interest lies in the identification of the effect of an action which means d…
stat.ML2018
Simplifying Probabilistic Expressions in Causal Inference
Santtu Tikka, Juha Karvanen
Obtaining a non-parametric expression for an interventional distribution is one of the most fundamental tasks in causal inference. Such an expression can be obtained for an identif…