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Many applications across sciences and technologies require a careful quantification of non-deterministic effects to a system output, for example when evaluating the system's reliability or when gearing it towards more robust operation conditions. At the he ...
We examine the cosmological information available from the 1-point probability density function (PDF) of the weak-lensing convergence field, utilizing fast L-PICOLA simulations and a Fisher analysis. We find competitive constraints in the Omega(m)-sigma(8) ...
Diffuse correlation spectroscopy (DCS) is the technique of choice for non-invasive assessments of human bone blood flow. However, DCS classical algorithms are based on the fundamental assumption that the electric field of the light reaching the DCS photode ...
The present contribution demonstrates the applicability of polynomial chaos expansion to stochastic (optimal) AC power flow problems that arise in the operation of power grids. For rectangular power flow, polynomial chaos expansion together with Galerkin p ...
Elliptical distributions are useful for modelling multivariate data, multivariate normal and Student t distributions being two special classes. In this paper, we provide a definition for the elliptical tempered stable (ETS) distribution based on its charac ...
Decision making and planning with partial state information is a problem faced by all forms of intelligent entities. The formulation of a problem under partial state information leads to an exorbitant set of choices with associated probabilistic outcomes m ...
Consider a max-stable process of the form , , where are points of the Poisson process with intensity u (-2)du on (0,a), X (i) , , are independent copies of a random d-variate vector X (that are independent of the Poisson process), and is a function. We sho ...
We address adaptive multivariate polynomial approximation by means of the discrete least-squares method with random evaluations, to approximate in the L2 probability sense a smooth function depending on a random variable distributed according to a given pr ...
A shape grammar defines a procedural shape space containing a variety of models of the same class, e.g. buildings, trees, furniture, airplanes, bikes, etc. We present a framework that enables a user to interactively design a probability density function (p ...
Understanding the dynamics driving the transformation of snowfall crystals into blowing snow particles is critical to correctly account for the energy and mass balances in polar and alpine regions. Here we propose a fragmentation theory of fractal snow cry ...