Quantification and Decomposition of Uncertainty Using Sliced-Normal Distribution: With Applications to NASA Data
This paper reformulates SN parameter estimation as a convex optimization problem over a positive semidefinite matrix, replacing the original nonconvex likelihood search with a formulation amenable to standard optimization tools, and clarify the expressive power of the SN class by connecting polynomial log-density model...