3 papers
math.ST2025
Statistical accuracy of the ensemble Kalman filter in the near-linear setting
E. Calvello, J. A. Carrillo, F. Hoffmann +3
Estimating the state of a dynamical system from partial and noisy observations is a ubiquitous problem in a large number of applications, such as probabilistic weather forecasting…
math.NA2024
Statistical Accuracy of Approximate Filtering Methods
J. A. Carrillo, F. Hoffmann, A. M. Stuart +1
Estimating the statistics of the state of a dynamical system, from partial and noisy observations, is both mathematically challenging and finds wide application. Furthermore, the a…
math.OC2022
The Mean Field Ensemble Kalman Filter: Near-Gaussian Setting
J. A. Carrillo, F. Hoffmann, A. M. Stuart +1
The ensemble Kalman filter is widely used in applications because, for high dimensional filtering problems, it has a robustness that is not shared for example by the particle filte…