Use of a Quantum Computer to do Importance and Metropolis-Hastings Sampling of a Classical Bayesian Network
arXiv:0811.1792
Abstract
Importance sampling and Metropolis-Hastings sampling (of which Gibbs sampling is a special case) are two methods commonly used to sample multi-variate probability distributions (that is, Bayesian networks). Heretofore, the sampling of Bayesian networks has been done on a conventional "classical computer". In this paper, we propose methods for doing importance sampling and Metropolis-Hastings sampling of a classical Bayesian network on a quantum computer.
41 pages (files: 1.tex, 3.sty, 8.eps)
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