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University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Sequential Monte Carlo methods for applications in Data Assimilation

## Sequential Monte Carlo methods for applications in Data AssimilationAdd to your list(s) Download to your calendar using vCal - Beskos, A (National University of Singapore)
- Wednesday 23 April 2014, 13:45-14:20
- Seminar Room 1, Newton Institute.
If you have a question about this talk, please contact Mustapha Amrani. Advanced Monte Carlo Methods for Complex Inference Problems Sequential Monte Carlo (SMC) methods are nowadays routinely applied in a variety of complex applications: hidden Markov models, dynamical systems, target tracking, control problems, just to name a few. Whereas SMC have been greatly refined in the last decades and are now much better understood, they are still known to suffer from the curse of dimensionality: algorithms can sometimes break down exponentially fast with the dimension of the state space. As a consequence, practitioners in high-dimensional Data Assimilation applications in atmospheric sciences, oceanography and elsewhere will typically use 3D-Var or Kalman-filter-type approximations that will provide biased estimates in the presence of non-linear model dynamics. The talk will concentrate on a class of SMC algorithms and will look at ways to reduce the cost of the algorithms as a function of the dimension of the state space. Explicit asymptotic results will clarify the effect of the dimension at the properties of the algorithm and could provide a platform for algorithmic optimisation in high dimensions. Applications will be shown in the context of Data Assimilation, in a problem where the objective is to target the posterior distribution of the initial condition of the Navier-Stokes equation given a Gaussian and noisy observations at different instances and locations of the spatial field. The dimension of the signal is in theory infinite-dimensional – in practice 64×64 or more depending on the resolution thus posing great challenges for the development and efficiency of SMC methods. This talk is part of the Isaac Newton Institute Seminar Series series. ## This talk is included in these lists:- All CMS events
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