HIGHLIGHTS
- who: Nonlin. Processes Geophys. and collaborators from the CEA-CNRS-UVSQ, Université and IPSL, Gif-sur-Yvette, France , LMD/IPSL, Ecole Normale Superieure, PSL research University, Paris, France have published the paper: Enhancing geophysical flow machine learning performance via scale separation, in the Journal: (JOURNAL) of 28/08/2021
- what: The authors investigate the applicability of such a framework to geophysical flows known to involve multiple scales in length time and energy and to feature intermittency. The authors show that both multiscale dynamics and intermittency introduce severe limitations to the applicability of recurrent neural networks . . .
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