31 citations as recorded by crossref.

1. Controlling balance in an ensemble Kalman filter G. Gottwald 10.5194/npg-21-417-2014
2. Low-rank statistical finite elements for scalable model-data synthesis C. Duffin et al. 10.1016/j.jcp.2022.111261
3. Cubature Ensemble Kalman Filter for Highly Dimensional Strongly Nonlinear Systems Q. Meng et al. 10.1109/ACCESS.2020.3014850
4. Derivation of ensemble Kalman–Bucy filters with unbounded nonlinear coefficients T. Lange 10.1088/1361-6544/ac4337
5. A shadowing-based inflation scheme for ensemble data assimilation T. Bellsky & L. Mitchell 10.1016/j.physd.2018.05.002
6. On the mathematical theory of ensemble (linear-Gaussian) Kalman–Bucy filtering A. Bishop & P. Del Moral 10.1007/s00498-023-00357-2
7. Divergence of the Ensemble Transform Kalman Filter (LETKF) by Nonlocal Observations A. Hutt 10.3389/fams.2020.00042
8. On the stability and the uniform propagation of chaos properties of Ensemble Kalman–Bucy filters P. Del Moral & J. Tugaut 10.1214/17-AAP1317
9. Probing robustness of nonlinear filter stability numerically using Sinkhorn divergence P. Mandal et al. 10.1016/j.physd.2023.133765
10. Multiscale Methods for Data Assimilation in Turbulent Systems Y. Lee & A. Majda 10.1137/140978326
11. Sequential assimilation of geomagnetic observations: perspectives for the reconstruction and prediction of core dynamics S. Sanchez et al. 10.1093/gji/ggz090
12. Preventing Catastrophic Filter Divergence Using Adaptive Additive Inflation for Baroclinic Turbulence Y. Lee et al. 10.1175/MWR-D-16-0121.1
13. An Approach for Filter Divergence Suppression in a Sequential Data Assimilation System and Its Application in Short-Term Traffic Flow Forecasting X. Tong et al. 10.3390/ijgi9060340
14. Estimating Time-Varying Applied Current in the Hodgkin-Huxley Model K. Campbell et al. 10.3390/app10020550
15. Ensemble Kalman filters for dynamical systems with unresolved turbulence I. Grooms et al. 10.1016/j.jcp.2014.05.037
16. Correcting Biased Observation Model Error in Data Assimilation T. Berry & J. Harlim 10.1175/MWR-D-16-0428.1
17. Concrete ensemble Kalman filters with rigorous catastrophic filter divergence D. Kelly et al. 10.1073/pnas.1511063112
18. Well-posedness and accuracy of the ensemble Kalman filter in discrete and continuous time D. Kelly et al. 10.1088/0951-7715/27/10/2579
19. Conditional Gaussian nonlinear system: A fast preconditioner and a cheap surrogate model for complex nonlinear systems N. Chen et al. 10.1063/5.0081668
20. Continuous data assimilation of large eddy simulation by lattice Boltzmann method and local ensemble transform Kalman filter (LBM-LETKF) Y. Hasegawa et al. 10.1088/1873-7005/ad06bd
21. A unified framework for the analysis of accuracy and stability of a class of approximate Gaussian filters for the Navier–Stokes equations A. Biswas & M. Branicki 10.1088/1361-6544/ad805b
22. The Mean-Field Ensemble Kalman Filter: Near-Gaussian Setting J. Carrillo et al. 10.1137/24M1628207
23. High-resolution data assimilation through stochastic subgrid tensor and parameter estimation from 4DEnVar Y. Yang & E. Memin 10.1080/16000870.2017.1308772
24. Ensemble data assimilation for earthquake sequences: probabilistic estimation and forecasting of fault stresses Y. van Dinther et al. 10.1093/gji/ggz063
25. $l_p$ Regularization for Ensemble Kalman Inversion Y. Lee 10.1137/20M1365168
26. On the Stability and the Uniform Propagation of Chaos of a Class of Extended Ensemble Kalman--Bucy Filters P. Del Moral et al. 10.1137/16M1087497
27. Kernel-based prediction of non-Markovian time series F. Gilani et al. 10.1016/j.physd.2020.132829
28. An approach to periodic, time-varying parameter estimation using nonlinear filtering A. Arnold & A. Lloyd 10.1088/1361-6420/aad3e0
29. Non-asymptotic analysis of ensemble Kalman updates: effective dimension and localization O. Al-Ghattas & D. Sanz-Alonso 10.1093/imaiai/iaad043
30. Predictions of the geomagnetic secular variation based on the ensemble sequential assimilation of geomagnetic field models by dynamo simulations S. Sanchez et al. 10.1186/s40623-020-01279-y
31. Multivariate localization functions for strongly coupled data assimilation in the bivariate Lorenz 96 system Z. Stanley et al. 10.5194/npg-28-565-2021