Work

Bayesian Networks

Year: 2007

Type: reference-entry

Abstract: Bayesian networks are probabilistic models based on direct acyclic graphs. These models enable a direct representation of causal relations between variables. Their structure is ideal for combining prior knowledge, which often comes in causal form, and observed data. This article gives a short description of the concepts of this important class of models that have become extremely popular in recent years.

Source: Wiley eBooks

Parent work: Encyclopedia of Statistics in Quality and Reliability

DOI: 10.1002/9780470061572.eqr089

Author: Irad Ben‐Gal

Institution: Tel Aviv University

Language: English

Topic: Bayesian Modeling and Causal Inference

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W3191596906

Cites: 19

Cited by: 390

Related to: 9