Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Many image formation processes are complex interactions of several sub-processes and the analysis of the resulting images requires often to separate the influence of these sub-pr...
In this paper, we propose a stochastic simulation to model and analyze cellular signal transduction. The high number of objects in a simulation requires advanced visualization tec...
Martin Falk, Michael Klann, Matthias Reuss, Thomas...
This is an extended version of an essay with the same title that I wrote for the workshop Algebraic Process Calculi: The First Twenty Five Years and Beyond, held in Bertinoro, Ita...
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 ...