This paper presents a hierarchical-compositional model of human faces, as a three-layer AND-OR graph to account for the structural variabilities over multiple resolutions. In the A...
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
Abstract Synchronising Graphs is a system of parallel graph transformation designed for modeling process interaction in a network environment. We propose a theory of context-free s...
A widely agreed upon definition of time series causality inference, established in the seminal 1969 article of Clive Granger (1969), is based on the relative ability of the histor...
Abstract. The specification of business processes is becoming a more and more critical aspect for organizations. Such processes are specified as workflow models expressing the logi...