A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to ...
Multiplicative noise (also known as speckle noise) models are central to the study of coherent imaging systems, such as synthetic aperture radar and sonar, and ultrasound and laser...
—Epidemic models based on nonlinear differential equations have been extensively applied in a variety of systems as diverse as infectious outbreaks, marketing, diffusion of belie...
When dealing with computationally expensive simulation codes or process measurement data, surrogate modeling methods are firmly established as facilitators for design space explor...
Dirk Gorissen, Ivo Couckuyt, Eric Laermans, Tom Dh...