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We discuss properties of hierarchical Bayesian inversion through the ensemble Kalman filter (EnKF).
Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics, Journal of Geophysical Research: Oceans
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Assimilation of geosataltimeter data for the agulhas currentusing the ensemble Kalman filter with a quasi-geostrophic model, Monthly Weather Review
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A regularizing Levenberg-Marquardt scheme, with applications to inverse groundwater filtration problems, Inverse Problems,
M. Hanke · 1997
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A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts, Monthly Weather Review
J. L. Anderson and S. L. Anderson · 1999
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An ensemble adjustment Kalman filter for data assimilation, Monthly Weather Review
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Non-centered parameterisations for hierarchical models and data augmentation, Bayesian statistics
O. Papaspiliopoulos, G. O. Roberts, and M. Sköld · 2003
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Accounting for error due to unresolved scales in ensemble data assimilation: a comparison of different approaches, Monthly Weather Review
T. M. Hamill and J. S. Whitaker · 2004
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Ensemble Kalman filter for automatic history matching of geologic facies, Journal of Petroleum Science and Engineering
N. Liu and D. S. Oliver · 2005
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A general framework for the parametrisation of hierarchical models, Statistical Science
O. Papaspiliopoulos, G. O. Roberts, and M. Sköld · 2007
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Data Assimilation: The Ensemble Kalman Filter
G. Evensen · 2009
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Iterative ensemble Kalman filters for data assimilation, SPE J
G. Li and A. C. Reynolds · 2009
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Inverse problems: A Bayesian perspective. Acta Numerica
A. M. Stuart · 2010
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Large sample asymptotics for the ensemble Kalman filter, The Oxford Handbook of Nonlinear Filtering
F. Le Gland, V. Monbet and V. D. Tran · 2011
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An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach, Volume 73
F. Lindgren, H. Rue and J. Lindström · 2011
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On the convergence of the ensemble Kalman filter, Applications of Mathematics
J. Mandel, L. Cobb, and J. D. Beezley · 2011
Hierarchical Bayesian Level Set Inversion, Statistics and Computing
M. M. Dunlop, M. A. Iglesias and A. M. Stuart · 2016
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A regularising iterative ensemble Kalman method for PDE-constrained inverse problems, Inverse Problems
M. A. Iglesias · 2016
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L. Roininen, M. Girolami, S. Lasanen and M. Markkanen · 2016
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Importance sampling: computational complexity and intrinsic dimension,, To appear in Statistical Science
S. Agapiou, O. Papaspiliopoulos, D. Sanz-Alonso and A. M. Stuart · 2017
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A strongly convergent numerical scheme from EnKF continuum analysis,
D. Blomker, C. Schillings and P. Wacker, · 2017
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Cited alongside, same era.
Analysis of the Gibbs sampler for hierarchical inverse problems, SIAM Journal on Uncertainty Quantification
S. Agapiou, J. M. Bardsley, O. Papaspiliopoulos and A. M. Stuart · 2014
Cited alongside, same era.
Ensemble Kalman methods for inverse problems. Inverse Problems
M. A. Iglesias, K. J. H. Law and A. M. Stuart · 2014
Cited alongside, same era.
Whittle-Matérn priors for Bayesian statistical inversion with applications in electrical impedance tomography, Inverse problems and Imaging
L. Roininen, J. M. J. Huttunen and S. Lasanen · 2014
Cited alongside, same era.
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Parameterizations for ensemble Kalman inversion
N. K. Chada, M. A. Iglesias, L. Roininen and A. M. Stuart · 2017
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W. Liu, J. Li and Y. M. Marzouk · 2017
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Analysis of the ensemble Kalman filter for inverse problems, SIAM Numerical Analysis (accepted)
C. Schillings and A. M. Stuart · 2017
Later among the works it cites.