Layout of Bayesian networks

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Authors:	Kim Marriott	Monash University, Australia
	Peter Moulder	Monash University, Australia
	Lucas Hope	Monash University, Australia
	Charles Twardy	Monash University, Australia

	2005 Article
Bibliometrics
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· Proceeding

ACSC '05 Proceedings of the Twenty-eighth Australasian conference on Computer Science - Volume 38

Pages 97-106
Australian Computer Society, Inc. Darlinghurst, Australia, Australia ©2005
table of contents ISBN:1-920-68220-1

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Bayesian network: A Bayesian network, Bayes network, belief network, Bayes(ian) model or probabilistic directed acyclic graphical model is a probabilistic graphical model (a type of statistical model) that represents a set of random variables and their conditional dependencies via a directed acyclic graph (DAG). For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms. more from Wikipedia
Directed acyclic graph: In mathematics and computer science, a directed acyclic graph, is a directed graph with no directed cycles. That is, it is formed by a collection of vertices and directed edges, each edge connecting one vertex to another, such that there is no way to start at some vertex v and follow a sequence of edges that eventually loops back to v again. DAGs may be used to model several different kinds of structure in mathematics and computer science. more from Wikipedia
Phase (waves): Phase in sinusoidal functions or in waves has two different, but closely related meanings. One is the initial angle of a sinusoidal function at its origin and is sometimes called phase offset. Another usage is the fraction of the wave cycle which has elapsed relative to the origin. more from Wikipedia