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A Comparison of Variational and Markov Chain Monte Carlo Methods for Inference in Partially Observed Stochastic Dynamic Systems

Shen, Y; Archambeau, C; Cornford, D; Opper, M; Shawe-Taylor, J; Barillec, R; (2010) A Comparison of Variational and Markov Chain Monte Carlo Methods for Inference in Partially Observed Stochastic Dynamic Systems. JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY , 61 (1) 51 - 59. 10.1007/s11265-008-0299-y.

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Type:Article
Title:A Comparison of Variational and Markov Chain Monte Carlo Methods for Inference in Partially Observed Stochastic Dynamic Systems
DOI:10.1007/s11265-008-0299-y
Keywords:Data assimilation, Signal processing, Nonlinear smoothing, Variational approximation, Bayesian computation
UCL classification:UCL > School of BEAMS > Faculty of Engineering Science > Computer Science

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