no code implementations • 25 Oct 2022 • Alban Farchi, Marcin Chrust, Marc Bocquet, Patrick Laloyaux, Massimo Bonavita
Data assimilation is used to estimate the system state from the observations, while machine learning computes a surrogate model of the dynamical system based on those estimated states.
no code implementations • 23 Jul 2021 • Alban Farchi, Marc Bocquet, Patrick Laloyaux, Massimo Bonavita, Quentin Malartic
We compare online and offline learning using the same framework with the two-scale Lorenz system, and show that with online learning, it is possible to extract all the information from sparse and noisy observations.
no code implementations • 23 Oct 2020 • Alban Farchi, Patrick Laloyaux, Massimo Bonavita, Marc Bocquet
This yields a class of iterative methods in which, at each iteration a DA step assimilates the observations, and alternates with a ML step to learn the underlying dynamics of the DA analysis.