Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
Abstract. The Unified Modelling Language (UML) is intended to describe systems, but it is not clear what systems satisfy a given collection of UML diagrams. Stephen Mellor has desc...
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
Software-defined networks (SDNs) are a new implementation architecture in which a controller machine manages a distributed collection of switches, by instructing them to install ...
Christopher Monsanto, Nate Foster, Rob Harrison, D...