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On the Incorporation of Box-Constraints for Ensemble Kalman Inversion · Around

2019

On the Incorporation of Box-Constraints for Ensemble Kalman Inversion

Chada, Neil K., Schillings, Claudia, Weissmann, Simon

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The Bayesian approach to inverse problems is widely used in practice to infer unknown parameters from noisy observations.

In this framework, the ensemble Kalman inversion has been successfully applied for the quantification of uncertainties in various areas of applications.
In recent years, a complete analysis of the method has been developed for linear inverse problems adopting an optimization viewpoint.
However, many applications require the incorporation of additional constraints on the parameters, e.g.

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