Symbolic Probabilistic Inference in Large BN20 Networks

D'Ambrosio, Bruce

doi:10.1016/B978-1-55860-332-5.50022-5

Symbolic Probabilistic Inference in Large BN20 Networks

Bruce D'Ambrosio

UAI 1994 pp. 128-135

doi:10.1016/B978-1-55860-332-5.50022-5 /uai/1994/daposambrosio1994uai-symbolic/

Abstract

A BN2O network is a two level belief net in which the parent interactions are modeled using the noisy-or interaction model. In this paper we discuss application of the SPI local expression language to efficient inference in large BN2O networks. In particular, we show that there is significant structure, which can be exploited to improve over the Quickscore result. We further describe how symbolic techniques can provide information which can significantly reduce the computation required for computing all cause posterior marginals. Finally, we present a novel approximation technique with preliminary experimental results.

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Cite

Text

D'Ambrosio. "Symbolic Probabilistic Inference in Large BN20 Networks." Conference on Uncertainty in Artificial Intelligence, 1994. doi:10.1016/B978-1-55860-332-5.50022-5

Markdown

[D'Ambrosio. "Symbolic Probabilistic Inference in Large BN20 Networks." Conference on Uncertainty in Artificial Intelligence, 1994.](https://mlanthology.org/uai/1994/daposambrosio1994uai-symbolic/) doi:10.1016/B978-1-55860-332-5.50022-5

BibTeX

@inproceedings{daposambrosio1994uai-symbolic,
  title     = {{Symbolic Probabilistic Inference in Large BN20 Networks}},
  author    = {D'Ambrosio, Bruce},
  booktitle = {Conference on Uncertainty in Artificial Intelligence},
  year      = {1994},
  pages     = {128-135},
  doi       = {10.1016/B978-1-55860-332-5.50022-5},
  url       = {https://mlanthology.org/uai/1994/daposambrosio1994uai-symbolic/}
}