Stochastic simulation models are used to predict the behavior of real systems whose components have random variation. The simulation model generates artificial random quantities b...
This paper addresses the problem of the optimal design of numerical experiments for the construction of nonlinear surrogate models. We describe a new method, called learner disagre...
In this paper, an edge-preserving nonlinear iterative regularization-based image resampling method for a single noise-free image is proposed. Several aspects of the resampling alg...
In this paper, we investigate the problem of deriving precision estimates for bootstrap quantities within parametric families. Efron's [1992] jackknife-after-bootstrap is a s...
—Image super-resolution is generally regarded as consisting of three steps – image registration, fusion, and deblurring. This paper presents a novel technique for resampling a ...