Biblio
Filters: Author is Julien Brajard [Clear All Filters]
Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization. Foundations of Data Science (FoDS) 2, (2020). Abstract
Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: A case study with the Lorenz 96 model. Journal of Computational Science 44, (2020).
Combining data assimilation and machine learning to infer unresolved scale parametrization. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 379, (2021). Abstract
Twenty-One Years of Phytoplankton Bloom Phenology in the Barents, Norwegian, and North Seas. Frontiers in Marine Science 8, (2021).
