Monte Carlo sampling has become a major vehicle for approximate inference in Bayesian networks. In this paper, we investigate a fam ily of related simulation approaches, known collectively as quasi-Monte Carlo methods based on deterministic low-discrepancy se quences. We first outline several theoreti cal aspects of deterministic low-discrepancy sequences, show three examples of such se que...
