Neural networks have become a prominent approach to solve inverse proble...
In this paper, we introduce several geometric characterizations for stro...
Neural networks have become a prominent approach to solve inverse proble...
In this paper, we consider the problem of phase retrieval, which consist...
We study a stochastic first order primal-dual method for solving
convex-...
In this paper, we study a non-local approximation of the time-dependent
...
Lipschitz continuity of the gradient mapping of a continuously different...
In this paper we study continuum limits of the discretized p-Laplacian
e...
In this paper we propose and analyze inexact and stochastic versions of ...
Discretized Langevin diffusions are efficient Monte Carlo methods for
sa...
In this paper, we consider a model called CHARME (Conditional Heterosced...
This paper provides a set of sensitivity analysis and activity identific...
We propose a unifying algorithm for non-smooth non-convex optimization. ...
Astronomical images suffer a constant presence of multiple defects that ...
In this paper, we develop an approach to recursively estimate the quadra...
In this paper, we propose to combine formally noise and shape priors in
...
In this paper, we focus on statistical region-based active contour model...