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Research talks;Probability and Statistics

Bayesian posterior distributions can be numerically intractable, even by the means of Markov Chain Monte Carlo methods. Bayesian variational methods can then be used to compute directly (and fast) a deterministic approximation of these posterior distributions. In this course, I describe the principles of the variational methods and their application in Bayesian inference, review main theoretical results and discuss their use on examples.

62F15 ; 62H12 ; 49J40

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