[Statlist] Next talk: Friday, November 30, 2012 (15.15h. - 16.15h), with Sebastian Reich, Universität Potsdam

[Cecilia Rey]

ETH and University of Zurich

Proff. P. Buehlmann -  L. Held - H.R. Kuensch -
M. Maathuis -  S. van de Geer - M. Wolf

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We are glad to announce the following talk
Friday, November 30, 2012, 15.15h, HG G 19.1

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by Sebastian Reich, Universität Potsdam


Titel:

Bayesian inference and sequential filtering: An optimal coupling of measures perspective

Abstract:

Sequential filtering relies on the propagation of uncertainty under a given model dynamics within a Monte Carlo (MC) setting combined with an assimilation of observations using Bayes' theorem. The recursive application of Bayes' theorem within a dynamic MC framework poses major computational challenges. The popular class of sequential Monte Carlo methods (SMCMs) relies on a proposal step and an importance resampling step. 
However, SMCMs are subject to the curse of dimensionality and alternative methods are needed for filtering in high-dimension. The ensemble Kalman filter (EnKF) has emerged as a promising alternative to SMCMs but is also known to lead to asymptotically inconsistent results. 
Following an introduction to sequential filtering, I will discuss a McKean approach to Bayesian inference and its implementation using optimal couplings. Applying this approach to the sequential filtering leads to new perspectives on both SMCMs and EnKFs as well as to novel filter algorithms.

The abstract is also to be found here:  http://stat.ethz.ch/events/research_seminar
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