research
∙
03/18/2023
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review
Data Assimilation (DA) and Uncertainty quantification (UQ) are extensive...
share
research
∙
10/25/2022
Online model error correction with neural networks in the incremental 4D-Var framework
Recent studies have demonstrated that it is possible to combine machine ...
research
∙
07/23/2021
State, global and local parameter estimation using local ensemble Kalman filters: applications to online machine learning of chaotic dynamics
In a recent methodological paper, we have shown how to learn chaotic dyn...
research
∙
07/23/2021
A comparison of combined data assimilation and machine learning methods for offline and online model error correction
Recent studies have shown that it is possible to combine machine learnin...
research
∙
10/23/2020
Using machine learning to correct model error in data assimilation and forecast applications
The idea of using machine learning (ML) methods to reconstruct the dynam...
research
∙
06/06/2020