Bayesian Inference Using the Proximal Mapping: Uncertainty Quantification Under Varying Dimensionality
{{output}}
In statistical applications, it is common to encounter parameters supported on a varying or unknown dimensional space. Examples include the fused lasso regression, the matrix recovery under an unknown low rank, etc. Despite the ease of obtaining a point estima... ...
