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An introduction to sequential Monte Carlo methods

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If you have a question about this talk, please contact Richard Samworth.

In this talk, we will introduce sequential Monte Carlo algorithms for sampling from a sequence of evolving distributions. We will mostly focus on the filtering problem, i.e., learning about the state of the system from currently available data, and issues such as algorithm degeneracy, and rejuvenation. Finally, we might discuss the problem of learning static parameters.

A comprehensive overview on this topic can be found here

This talk is part of the Statistics Reading Group series.

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