68 citations · 169 across the 22 of their papers we have counts for
4 papers · 1 filter
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…
OPM, a collection of Optimization Problems in Matlab
Serge Gratton, Philippe L. Toint
OPM is a small collection of CUTEst unconstrained and bound-constrained nonlinear optimization problems, which can be used in Matlab for testing optimization algorithms directly (i…
Adaptive Regularization Minimization Algorithms with Non-Smooth Norms and Euclidean Curvature
Serge Gratton, Philippe L. Toint
A regularization algorithm (AR1pGN) for unconstrained nonlinear minimization is considered, which uses a model consisting of a Taylor expansion of arbitrary degree and regularizati…
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…