10 citations · 11 across the 4 of their papers we have counts for
4 papers
Neural Fields for Fast and Scalable Interpolation of Geophysical Ocean Variables
J. Emmanuel Johnson, Redouane Lguensat, Ronan Fablet +2
Optimal Interpolation (OI) is a widely used, highly trusted algorithm for interpolation and reconstruction problems in geosciences. With the influx of more satellite missions, we h…
Filtering Internal Tides From Wide-Swath Altimeter Data Using Convolutional Neural Networks
Redouane Lguensat, Ronan Fablet, Julien Le Sommer +5
The upcoming Surface Water Ocean Topography (SWOT) satellite altimetry mission is expected to yield two-dimensional high-resolution measurements of Sea Surface Height (SSH), thus a…
Learning Generalized Quasi-Geostrophic Models Using Deep Neural Numerical Models
Redouane Lguensat, Julien Le Sommer, Sammy Metref +2
We introduce a new strategy designed to help physicists discover hidden laws governing dynamical systems. We propose to use machine learning automatic differentiation libraries to…
Towards the assimilation of satellite reflectance into semi-distributed ensemble snowpack simulations
Bertrand Cluzet, Jesus Revuelto, Matthieu Lafaysse +5
Uncertainties of snowpack models and of their meteorological forcings limit their use by avalanche hazard forecasters, or for glaciological and hydrological studies. The spatialize…