Causal inference with Bayes rule

Finn Lattimore, a Gradient Principal Researcher, has published her work on developing a Bayesian approach to inferring the impact of interventions or actions. The work, done jointly with David Rohde (Criteo AI Lab), shows 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. The work is available on Arxiv as two papers: Replacing the do calculus with Bayes rule, and Causal inference with Bayes rule. Finn and David have also created a video presentation Bayesian Causality.