68 citations · 169 across the 22 of their papers we have counts for
4 papers · 1 filter
A Block-Coordinate Approach of Multi-level Optimization with an Application to Physics-Informed Neural Networks
Serge Gratton, Valentin Mercier, Elisa Riccietti +1
Multi-level methods are widely used for the solution of large-scale problems, because of their computational advantages and exploitation of the complementarity between the involved…
A coarse space acceleration of deep-DDM
Valentin Mercier, Serge Gratton, Pierre Boudier
The use of deep learning methods for solving PDEs is a field in full expansion. In particular, Physical Informed Neural Networks, that implement a sampling of the physical domain a…
Latent Space Data Assimilation by using Deep Learning
Mathis Peyron, Anthony Fillion, Selime Gürol +4
Performing Data Assimilation (DA) at a low cost is of prime concern in Earth system modeling, particularly at the time of big data where huge quantities of observations are availab…
Data Assimilation Networks
Pierre Boudier, Anthony Fillion, Serge Gratton +2
Data assimilation (DA) aims at forecasting the state of a dynamical system by combining a mathematical representation of the system with noisy observations taking into account thei…