International audienceWe discuss recent results on sparse recovery for inverse potential problem with source term in divergence form. The notion of sparsity which is set forth is measure-theoretic, namely pure 1-unrectifiability of the support. The theory applies when a superset of the support is known to be slender, meaning it has measure zero and all connected components of its complement has infinite measure in R^3. We also discuss open issues in the non-slender case
In this thesis, we investigate nonstandard methods for the stable solution of the inverse medium pro...
International audienceWe study inverse problems for the Poisson equation with source term ...
Whatever the field of application, optimizing the results and sometimes even solving problems requir...
International audienceWe discuss recent results on sparse recovery for inverse potential problem wit...
International audienceThe present document is a slightly extended version of the article published i...
International audienceSparsity constraints are now very popular to regularize inverse problems. We r...
International audienceWe investigate the computational performance of the sparse vs cosparse regular...
This chapter is concerned with two important topics in the context of sparse recovery in inverse and...
International audienceSolving an underdetermined inverse problem implies the use of a regularization...
Inverse problems are problems where we want to estimate the values of certain parameters of a system...
International audienceThis paper investigates the problem of designing a deterministic system matrix...
International audienceSparse data models are powerful tools for solving ill-posed inverse problems. ...
We explore the possibility for using boundary measurements to recover a sparse source term f(x) in t...
In this thesis, we investigate nonstandard methods for the stable solution of the inverse medium pro...
International audienceWe study inverse problems for the Poisson equation with source term ...
Whatever the field of application, optimizing the results and sometimes even solving problems requir...
International audienceWe discuss recent results on sparse recovery for inverse potential problem wit...
International audienceThe present document is a slightly extended version of the article published i...
International audienceSparsity constraints are now very popular to regularize inverse problems. We r...
International audienceWe investigate the computational performance of the sparse vs cosparse regular...
This chapter is concerned with two important topics in the context of sparse recovery in inverse and...
International audienceSolving an underdetermined inverse problem implies the use of a regularization...
Inverse problems are problems where we want to estimate the values of certain parameters of a system...
International audienceThis paper investigates the problem of designing a deterministic system matrix...
International audienceSparse data models are powerful tools for solving ill-posed inverse problems. ...
We explore the possibility for using boundary measurements to recover a sparse source term f(x) in t...
In this thesis, we investigate nonstandard methods for the stable solution of the inverse medium pro...
International audienceWe study inverse problems for the Poisson equation with source term ...
Whatever the field of application, optimizing the results and sometimes even solving problems requir...