Bayesian Approaches to Inverse Problems with deep learning-based priors

Quand : 15 septembre 2026 à 11:15

Où : 1R3, 1er étage

Organisé par : Institut Henri Poincaré

Inverse problems are ubiquitous in signal and image processing. As inverse problems are known to be ill-posed or, at least, ill-conditioned, they require regularization through the introduction of additional constraints to mitigate the lack of information provided by the observations. A common difficulty lies in selecting an appropriate regularizer, which has a decisive influence on the quality of