A Fixed-Parameter Tractable Algorithm for Counting Markov Equivalence Classes with the same Skeleton

arXiv:2310.04218v2 Announce Type: replace-cross
Abstract: Causal DAGs (also known as Bayesian networks) are a popular tool for encoding conditional dependencies between random variables. In a causal DAG, the random variables are modeled as vertices in the DAG, and it is stipulated that every random variable is independent of its ancestors conditioned on its parents. It is possible, however, for two different causal DAGs on the same set of random variables to encode exactly the same set of conditional dependencies. Such …

abstract algorithm arxiv bayesian cs.ai cs.ds cs.lg dag dependencies encoding every independent markov networks popular random tool tractable type variables