Bayesian Artificial Intelligence

@article{Jensen2004BayesianAI,
  title={Bayesian Artificial Intelligence},
  author={F. Jensen},
  journal={Pattern Analysis and Applications},
  year={2004},
  volume={7},
  pages={221-223}
}
  • F. Jensen
  • Published 2004
  • Computer Science
  • Pattern Analysis and Applications
Kevin Korb and Ann Nicholson are experienced researchers in Bayesian networks. They have contributed to the theoretical development of the field, and they have several application projects behind them. This is apparent in their textbook, Bayesian Artificial Intelligence. It is a well written introduction to the field, and it contains many useful guidelines for building Bayesian network models. You cannot be successful in this field without a good insight into the mathematical theory behind it… Expand
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References

Causality: Models, Reasoning and Inference
  • 9,995
  • PDF