Conventional methods for state space exploration are limited to the analysis of small systems because they suffer from excessive memory and computational requirements. We have dev...
William J. Knottenbelt, Peter G. Harrison, Mark Me...
We present a translation of a generic stochastic process algebra model into a form suitable for stochastic simulation. By systematically generating rate equations from a process d...
Jeremy T. Bradley, Stephen T. Gilmore, Nigel Thoma...
State space methods have proven indispensable in neural data analysis. However, common methods for performing inference in state-space models with non-Gaussian observations rely o...
Liam Paninski, Yashar Ahmadian, Daniel Gil Ferreir...
Abstract. Recently, there is an explosive development of fluid approaches to computer and distributed systems. These approaches are inherently stochastic and generate continuous st...