822 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of ReadingGB12 papers
- California Institute of TechnologyUS8 papers
- Fermi National Accelerator LaboratoryUS6 papers
- University of LeicesterGB6 papers
- Columbia UniversityUS5 papers
- Princeton UniversityUS5 papers
- Stanford UniversityUS5 papers
- University College LondonGB5 papers
- Utrecht UniversityNL5 papers
- Centre National de la Recherche ScientifiqueFR4 papers
- Institute for High Energy PhysicsES4 papers
- Kavli Institute for the Physics and Mathematics of the UniverseJP4 papers
Showing stat.MLShow all
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stat.ML2020★ 99 cited
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★ 206 cited
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…