156 citations · 304 across the 13 of their papers we have counts for
Showing 2020Show all
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stat.ML2020★ 156 cited
Using machine learning to correct model error in data assimilation and forecast applications
Alban Farchi, Patrick Laloyaux, Massimo Bonavita +1
The idea of using machine learning (ML) methods to reconstruct the dynamics of a system is the topic of recent studies in the geosciences, in which the key output is a surrogate mo…
stat.ML2020★ 35 cited
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…