In this paper Hidden Markov Model algorithms are considered as a method for computing conditional properties of continuous-time stochastic simulation models. The goal is to develo...
Fabian Wickborn, Claudia Isensee, Thomas Simon, Sa...
This paper investigates the rate of convergence of an alternative approximation method for stochastic differential equations. The rates of convergence of the one-step and multi-st...
In this paper we consider the modeling of a selected portion of signal transduction events involved in the angiogenesis process. The detailed model of this process contains a large...
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
Manufacturing processes are a key source of faults in complex hardware systems. Minimizing this impact of manufacturing uncertainties is one way towards achieving fault tolerant s...