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- W4288099500 abstract "The ensemble Kalman filter is a well-known and celebrated data assimilation algorithm. It is of particular relevance as it used for high-dimensional problems, by updating an ensemble of particles through a sample mean and covariance matrices. In this chapter we present a relatively recent topic which is the application of the EnKF to inverse problems, known as ensemble Kalman Inversion (EKI). EKI is used for parameter estimation, which can be viewed as a black-box optimizer for PDE-constrained inverse problems. We present in this chapter a review of the discussed methodology, while presenting emerging and new areas of research, where numerical experiments are provided on numerous interesting models arising in geosciences and numerical weather prediction." @default.
- W4288099500 created "2022-07-28" @default.
- W4288099500 creator A5089326886 @default.
- W4288099500 date "2022-07-26" @default.
- W4288099500 modified "2023-10-16" @default.
- W4288099500 title "A Review of the EnKF for Parameter Estimation" @default.
- W4288099500 doi "https://doi.org/10.48550/arxiv.2207.12802" @default.
- W4288099500 hasPublicationYear "2022" @default.
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