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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...
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11/17/2022
Learning 4DVAR inversion directly from observations
Variational data assimilation and deep learning share many algorithmic a...
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04/26/2021
Bridging observation, theory and numerical simulation of the ocean using Machine Learning
Progress within physical oceanography has been concurrent with the incre...
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12/09/2020
Fusion of rain radar images and wind forecasts in a deep learning model applied to rain nowcasting
Short or mid-term rainfall forecasting is a major task for several envir...
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09/09/2020
Combining data assimilation and machine learning to infer unresolved scale parametrisation
In recent years, machine learning (ML) has been proposed to devise data-...
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01/17/2020
Bayesian inference of dynamics from partial and noisy observations using data assimilation and machine learning
The reconstruction from observations of high-dimensional chaotic dynamic...
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01/06/2020
Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: a case study with the Lorenz 96 model
A novel method, based on the combination of data assimilation and machin...
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03/18/2019
Representing ill-known parts of a numerical model using a machine learning approach
In numerical modeling of the Earth System, many processes remain unknown...
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02/26/2019