Prune Sampling is a new MCMC method for discrete Bayesian networks that provably converges to the posterior distribution even under determinism, though it trails standard methods on large networks.
Giss: Combining gibbs sampling and samplesearch for inference in mixed probabilistic and deter- ministic graphical models
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Prune Sampling: a MCMC inference technique for discrete and deterministic Bayesian networks
Prune Sampling is a new MCMC method for discrete Bayesian networks that provably converges to the posterior distribution even under determinism, though it trails standard methods on large networks.