In Libra, each probabilistic model represents a probability distribution, P (X ), over set of discrete random variables, X = {X1, X2, . . . , Xn}. Libra supports Bayesian networks (BNs), Markov networks (MNs), dependency networks (DNs) [8], sumproduct networks (SPNs) [19], arithmetic circuits (ACs) [6], and mixtures of trees (MT) [17]. BNs and DNs represent a probability distribution as a colle...