This work develops a new multifidelity ensemble Kalman filter (MFEnKF) algorithm based on
a linear control variate framework. The approach allows for rigorous multifidelity extensions …

In this paper the filtering of partially observed diffusions, with discrete-time observations, is
considered. It is assumed that only biased approximations of the diffusion can be obtained …

This article reviews the application of some advanced Monte Carlo techniques in the context
of multilevel Monte Carlo (MLMC). MLMC is a strategy employed to compute expectations …

Abstract Multilevel Monte Carlo is a key tool for approximating integrals involving expensive
scientific models. The idea is to use approximations of the integrand to construct an …

We introduce a new multilevel ensemble Kalman filter method (MLEnKF) which consists of a
hierarchy of independent samples of ensemble Kalman filters (EnKF). This new MLEnKF …

Coastal zones are vulnerable to both erosion and flood risk, which can be assessed using
coupled hydro-morphodynamic models. However, the use of such models as decision …

In this work we combine ideas from multi-index Monte Carlo and ensemble Kalman filtering
(EnKF) to produce a highly efficient filtering method called multi-index EnKF (MIEnKF) …

Multifidelity methods aim to leverage the availability of models at different levels of fidelity
describing the same physical phenomena and are receiving growing attention in …

We introduce a new multilevel ensemble Kalman filtering method (MLEnKF) which consists
of a hierarchy of samples of the ensemble Kalman filter method (EnKF) using local-level …

There once was a dream that data-driven models would replace their theory-guided
counterparts. We have awoken from this dream. We now know that data cannot replace …