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University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Data assimilation: A dynamic homotopy-based coupling approach
Data assimilation: A dynamic homotopy-based coupling approachAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact nobody. GFDW02 - Forecast Verification and Data Assimilation in intermediate and large scale models of geophysical fluid dynamics, with applications to medium range and seasonal forecasting Homotopy approaches to Bayesian inference have found widespread use especially if the Kullback-Leibler divergence between the prior and the posterior distribution is large. Here we extend one of these homotopy approach to include an underlying stochastic diffusion process. The underlying mathematical problem is closely related to the Schrödinger bridge problem for given marginal distributions. We demonstrate that the proposed homotopy approach provides a computationally tractable approximation to the underlying bridge problem. In particular, our implementation builds upon the widely used ensemble Kalman filter methodology and extends it to Schrödinger bridge problems within the context of sequential data assimilation. This talk is part of the Isaac Newton Institute Seminar Series series. This talk is included in these lists:
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