This paper adresses the variance quantification problem for system identification based on the prediction error framework. The role of input and model class selection for the auto-...
In this paper, we propose a novel method for solving single-image super-resolution problems. Given a low-resolution image as input, we recover its highresolution counterpart using...
This paper describes a knowledge unit and the use of a software tool, DesignMentor, for teaching a very challenging topic in computer graphics and visualization, namely: curve and...
We investigate theoretically some properties of variational Bayes approximations based on estimating the mixing coefficients of known densities. We show that, with probability 1 a...
In this paper we study the problem of bivariate density estimation. The aim is to find a density function with the smallest number of local extreme values which is adequate with ...