Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
— In this paper we present an approach for localizing a sensor network augmented with a mobile robot which is capable of providing inter-sensor pose estimates through its odometr...
David Meger, Dimitri Marinakis, Ioannis M. Rekleit...
We propose an approach for timing analysis of software-based embedded computer systems that builds on the established probabilistic framework of Bayesian networks. We envision an ...
Parameterized model checking refers to any method that extends traditional, finite-state model checking to handle systems arbitrary number of processes. One popular approach to thi...
Abstract. Variant parametric types (VPT) represent the successful result of combining subtype polymorphism with parametric polymorphism to support a more flexible subtyping for Ja...