Browsing Geophysical Institute by Journals "Nonlinear processes in geophysics"
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Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models
(Peer reviewed; Journal article, 2019)Recent progress in machine learning has shown how to forecast and, to some extent, learn the dynamics of a model from its output, resorting in particular to neural networks and deep learning techniques. We will show how ... -
Data assimilation using adaptive, non-conservative, moving mesh models
(Peer reviewed; Journal article, 2019)Numerical models solved on adaptive moving meshes have become increasingly prevalent in recent years. Motivating problems include the study of fluids in a Lagrangian frame and the presence of highly localized structures ...