A Bayesian Knowledge Base is a generalization of traditional Bayesian Networks where nodes or groups of nodes have independence. In this paper we describe a method of generating a ...
In this paper we consider a problem that occurs when drawing public transportation networks. Given an embedded graph G = (V, E) (e.g. the railroad network) and a set H of paths in...
Matthew Asquith, Joachim Gudmundsson, Damian Merri...
We study the intrinsic difficulty of solving linear parabolic initial value problems numerically at a single point. We present a worst case analysis for deterministic as well as fo...
Almost all of the most successful quantum algorithms discovered to date exploit the ability of the Fourier transform to recover subgroup structure of functions, especially periodi...
Although it is acknowledged that multi-way dataflow constraints are useful in interactive applications, concerns about their tractability have hindered their acceptance. Certain l...