55 citations · 93 across the 4 of their papers we have counts for
5 papers
Online model error correction with neural networks in the incremental 4D-Var framework
Alban Farchi, Marcin Chrust, Marc Bocquet +2
Recent studies have demonstrated that it is possible to combine machine learning with data assimilation to reconstruct the dynamics of a physical model partially and imperfectly ob…
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…
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…
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…
Precision reconstruction of the dark matter-neutrino relative velocity from N-body simulations
Derek Inman, J. D. Emberson, Ue-Li Pen +3
Discovering the mass of neutrinos is a principle goal in high energy physics and cosmology. In addition to cosmological measurements based on two-point statistics, the neutrino mas…