Abstract:Abstract. Identification of unknown parameters on the basis of partial and noisy data is a challenging task, in particular in high dimensional and non-linear settings. Gaussian approximations to the problem, such as ensemble Kalman inversion, tend to be robust and computationally cheap and often produce astonishingly accurate estimations despite the simplifying underlying assumptions.
Yet there is a lot of room for improvement, specifically regarding a correct approximation of a non-Gaussian posterior distribu… Show more
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