Abstract. This contribution presents a novel approach to the challenging problem of model selection in motion estimation from sequences of images. New light is cast on parametric m...
We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The paramete...
Matthias Seeger, Sebastian Gerwinn, Matthias Bethg...
We review state-space control models in order to identify timing properties that can favour flexible scheduling of real-time control tasks. First, from the state-space model of a ...
— In this paper a dynamic contact model is presented based on the Johnson-Kendall-Roberts (JKR) theory. The classical JKR model captures the contact properties for the quasi-stat...
As systems evolve, they become harder to understand because the implementation of concepts (e.g. business rules) becomes less coherent. To preserve source code comprehensibility, ...