5 papers
Quantitative Wasserstein Propagation of Chaos for Transport Ensemble Filters
Frederic J. N. Jorgensen, Ricardo Baptista, Franca Hoffmann +1
We develop a general probabilistic framework for analyzing propagation of chaos in transport ensemble filters (TEFs), a broad class of interacting particle systems that are used to…
Large-time behavior and accuracy of the Mean-Field Ensemble Kalman Filter in the Linear Detectable Setting
Franca Hoffmann, Sangmin Park, Andrew M. Stuart
The ensemble Kalman filter (EnKF), originally developed in the geophysical sciences, is now widely used for state and parameter estimation problems in various domains of applicatio…
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…
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…
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…