49 citations · 54 across the 5 of their papers we have counts for
7 papers
Precipitaion Nowcasting using Deep Neural Network
Mohamed Chafik Bakkay, Mathieu Serrurier, Valentin Kivachuk Burda +8
Precipitation nowcasting is of great importance for weather forecast users, for activities ranging from outdoor activities and sports competitions to airport traffic management. In…
ARPEGE Cloud Cover Forecast Post-Processing with Convolutional Neural Network
Florian Dupuy, Olivier Mestre, Mathieu Serrurier +7
Cloud cover is crucial information for many applications such as planning land observation missions from space. It remains however a challenging variable to forecast, and Numerical…
Surrogate Models for Rainfall Nowcasting
Naty Citlali Cabrera-Gutiérrez, Hadrien Godé, Jean-Christophe Jouhaud +8
Nowcasting (or short-term weather forecasting) is particularly important in the case of extreme events as it helps prevent human losses. Many of our activities, however, also depen…
Improved Surrogate Modeling using Machine Learning for Industrial Civil Aircraft Aerodynamics
Romain Dupuis, Jean-Christophe Jouhaud, Pierre Sagaut
Predicting and simulating aerodynamic fields for civil aircraft over wide flight envelopes represent a real challenge mainly due to significant numerical costs and complex flows. S…
Surrogate Modeling of Aerodynamic Simulations for Multiple Operating Conditions Using Machine Learning
Romain Dupuis, Jean-Christophe Jouhaud, Pierre Sagaut
This article presents an original methodology for the prediction of steady turbulent aerodynamic fields. Due to the important computational cost of high-fidelity aerodynamic simula…
Sounding Spider: An Efficient Way for Representing Uncertainties in High Dimensions
Pamphile T. Roy, Sophie Ricci, Bénédicte Cuenot +1
This article proposes a visualization method for multidimensional data based on: (i) Animated functional Hypothetical Outcome Plots (f-HOPs); (ii) 3-dimensional Kiviat plot; and (i…