research
∙
07/15/2023
Accuracy Controlled Schemes for the Eigenvalue Problem of the Radiative Transfer Equation
The criticality problem in nuclear engineering asks for the principal ei...
share
research
∙
02/10/2023
Approximation and Structured Prediction with Sparse Wasserstein Barycenters
We develop a general theoretical and algorithmic framework for sparse ap...
research
∙
11/19/2022
Moment-SoS Methods for Optimal Transport Problems
Most common Optimal Transport (OT) solvers are currently based on an app...
research
∙
09/19/2022
Nonlinear approximation spaces for inverse problems
This paper is concerned with the ubiquitous inverse problem of recoverin...
research
∙
05/05/2022
Waserstein model reduction approach for parametrized flow problems in porous media
The aim of this work is to build a reduced-order model for parametrized ...
research
∙
03/15/2022
Inverse Problems: A Deterministic Approach using Physics-Based Reduced Models
These lecture notes summarize various summer schools that I have given o...
research
∙
06/17/2021
State Estimation with Model Reduction and Shape Variability. Application to biomedical problems
We develop a mathematical and numerical framework to solve state estimat...
research
∙
09/19/2020
Epidemiological short-term Forecasting with Model Reduction of Parametric Compartmental Models. Application to the first pandemic wave of COVID-19 in France
We propose a forecasting method for predicting epidemiological health se...
research
∙
09/06/2020
Nonlinear reduced models for state and parameter estimation
State estimation aims at approximately reconstructing the solution u to ...
research
∙
07/05/2020
Depth-Adaptive Neural Networks from the Optimal Control viewpoint
In recent years, deep learning has been connected with optimal control a...
research
∙
06/07/2020
