157 citations · 340 across the 7 of their papers we have counts for
3 papers · 1 filter
State, global and local parameter estimation using local ensemble Kalman filters: applications to online machine learning of chaotic dynamics
Quentin Malartic, Alban Farchi, Marc Bocquet
In a recent methodological paper, we showed how to learn chaotic dynamics along with the state trajectory from sequentially acquired observations, using local ensemble Kalman filte…
A comparison of combined data assimilation and machine learning methods for offline and online model error correction
Alban Farchi, Marc Bocquet, Patrick Laloyaux +2
Recent studies have shown that it is possible to combine machine learning methods with data assimilation to reconstruct a dynamical system using only sparse and noisy observations…
Online learning of both state and dynamics using ensemble Kalman filters
Marc Bocquet, Alban Farchi, Quentin Malartic
The reconstruction of the dynamics of an observed physical system as a surrogate model has been brought to the fore by recent advances in machine learning. To deal with partial and…