Abstract:Abstract. Identification of unknown parameters on the basis of partial and noisy data is a challenging task in particular in high dimensional and nonlinear settings. Gaussian approximations to the problem, such as ensemble Kalman inversion, tend to be robust, computationally cheap and often produce astonishingly accurate estimations despite the inherently wrong underlying assumptions. Yet there is a lot of room for improvement specifically regarding the description of the associated statistics. The tempered en… Show more
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