A Generalization of the Noisy-or Model

UAI 1993 pp. 208-218

doi:10.1016/B978-1-4832-1451-1.50030-5 /uai/1993/srinivas1993uai-generalization/

Abstract

The Noisy-Or model is convenient for describing a class of uncertain relationships in Bayesian networks [Pearl 1988]. Pearl describes the Noisy-Or model for Boolean variables. Here we generalize the model to nary input and output variables and to arbitrary functions other than the Boolean OR function. This generalization is a useful modeling aid for construction of Bayesian networks. We illustrate with some examples including digital circuit diagnosis and network reliability analysis.

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Text

Srinivas. "A Generalization of the Noisy-or Model." Conference on Uncertainty in Artificial Intelligence, 1993. doi:10.1016/B978-1-4832-1451-1.50030-5

Markdown

[Srinivas. "A Generalization of the Noisy-or Model." Conference on Uncertainty in Artificial Intelligence, 1993.](https://mlanthology.org/uai/1993/srinivas1993uai-generalization/) doi:10.1016/B978-1-4832-1451-1.50030-5

BibTeX

@inproceedings{srinivas1993uai-generalization,
  title     = {{A Generalization of the Noisy-or Model}},
  author    = {Srinivas, Sampath},
  booktitle = {Conference on Uncertainty in Artificial Intelligence},
  year      = {1993},
  pages     = {208-218},
  doi       = {10.1016/B978-1-4832-1451-1.50030-5},
  url       = {https://mlanthology.org/uai/1993/srinivas1993uai-generalization/}
}