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stat.ML2020
Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization
Marc Bocquet, Julien Brajard, Alberto Carrassi +1
The reconstruction from observations of high-dimensional chaotic dynamics such as geophysical flows is hampered by (i) the partial and noisy observations that can realistically be…
stat.ML2020
Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: a case study with the Lorenz 96 model
Julien Brajard, Alberto Carassi, Marc Bocquet +1
A novel method, based on the combination of data assimilation and machine learning is introduced. The new hybrid approach is designed for a two-fold scope: (i) emulating hidden, po…