17 citations · 26 across the 3 of their papers we have counts for
3 papers
A Computational Framework and Implementation of Implicit Priors in Bayesian Inverse Problems
Jasper M. Everink, Chao Zhang, Amal M. A. Alghamdi +3
Solving Bayesian inverse problems typically involves deriving a posterior distribution using Bayes' rule, followed by sampling from this posterior for analysis. Sampling methods, s…
On Maximum-a-Posteriori estimation with Plug & Play priors and stochastic gradient descent
Rémi Laumont, Valentin de Bortoli, Andrés Almansa +3
Bayesian methods to solve imaging inverse problems usually combine an explicit data likelihood function with a prior distribution that explicitly models expected properties of the…
Bayesian imaging using Plug & Play priors: when Langevin meets Tweedie
Rémi Laumont, Valentin de Bortoli, Andrés Almansa +3
Since the seminal work of Venkatakrishnan et al. in 2013, Plug & Play (PnP) methods have become ubiquitous in Bayesian imaging. These methods derive Minimum Mean Square Error (MMSE…