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Ronan Fablet

IMT Atlantique, Lab-STICC, UMR CNRS, France

Inversion of sea surface currents from satellite-derived SST-SSH synergies with 4DVarNets


Nov 23, 2022
Ronan Fablet, Bertrand Chapron, Julien Le Sommer, Florian Sévellec

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Neural Fields for Fast and Scalable Interpolation of Geophysical Ocean Variables


Nov 18, 2022
J. Emmanuel Johnson, Redouane Lguensat, Ronan Fablet, Emmanuel Cosme, Julien Le Sommer

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* Machine Learning and the Physical Sciences workshop, NeurIPS 2022 

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Deep learning for Lagrangian drift simulation at the sea surface


Nov 17, 2022
Daria Botvynko, Carlos Granero-Belinchon, Simon Van Gennip, Abdesslam Benzinou, Ronan Fablet

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Learning Neural Optimal Interpolation Models and Solvers


Nov 14, 2022
Maxime Beauchamp, Joseph Thompson, Hugo Georgenthum, Quentin Febvre, Ronan Fablet

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4DVarNet-SSH: end-to-end learning of variational interpolation schemes for nadir and wide-swath satellite altimetry


Nov 10, 2022
Maxime Beauchamp, Quentin Febvre, Hugo Georgentum, Ronan Fablet

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Learning-based estimation of in-situ wind speed from underwater acoustics


Aug 18, 2022
Matteo Zambra, Dorian Cazau, Nicolas Farrugia, Alexandre Gensse, Sara Pensieri, Roberto Bozzano, Ronan Fablet

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* 13 pages, 5 figures 

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Rain Rate Estimation with SAR using NEXRAD measurements with Convolutional Neural Networks


Jul 15, 2022
Aurélien Colin, Pierre Tandeo, Charles Peureux, Romain Husson, Nicolas Longepe, Ronan Fablet

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* 25 pages, 10 figures 

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Multimodal 4DVarNets for the reconstruction of sea surface dynamics from SST-SSH synergies


Jul 04, 2022
Ronan Fablet, Quentin Febvre, Bertrand Chapron

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A posteriori learning for quasi-geostrophic turbulence parametrization


Apr 08, 2022
Hugo Frezat, Julien Le Sommer, Ronan Fablet, Guillaume Balarac, Redouane Lguensat

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* 36 pages, 14 figures, submitted to Journal of Advances in Modeling Earth Systems (JAMES) 

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Multimodal learning-based inversion models for the space-time reconstruction of satellite-derived geophysical fields


Mar 20, 2022
Ronan Fablet, Bertrand Chapron

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