2 papers
math.ST2023
Sparse Bayesian Inference with Regularized Gaussian Distributions
Jasper Marijn Everink, Yiqiu Dong, Martin Skovgaard Andersen
Regularization is a common tool in variational inverse problems to impose assumptions on the parameters of the problem. One such assumption is sparsity, which is commonly promoted…
stat.CO2022
Horseshoe priors for edge-preserving linear Bayesian inversion
Felipe Uribe, Yiqiu Dong, Per Christian Hansen
In many large-scale inverse problems, such as computed tomography and image deblurring, characterization of sharp edges in the solution is desired. Within the Bayesian approach to…