Active Structure Learning of Causal DAGs via Directed Clique Trees

Neural Information Processing Systems 

A growing body of work has begun to study intervention design for efficient structure learning of causal directed acyclic graphs (DAGs). A typical setting is a causally sufficient setting, i.e. a system with no latent confounders, selection

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