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Causal Inference with Bayes Rule

An in-depth look at modelling interventions: joint work between Finn Lattimore (Gradient Institute) & David Rohde (Criteo AI Lab) Articles
Dec 13, 2019
Technical audience

In this post we explain a Bayesian approach to inferring the impact of interventions or actions. We show that representing causality within a standard Bayesian approach softens the boundary between tractable and impossible queries and opens up potential new approaches to causal inference. This post is a detailed but informal presentation of our Arxiv papers: Replacing the do calculus with Bayes rule, and Causal inference with Bayes rule - also see our video presentation Bayesian Causality

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