Probabilistic inference in graphical models

@inproceedings{Jordan2004ProbabilisticII,
  title={Probabilistic inference in graphical models},
  author={Michael I. Jordan},
  year={2004}
}
Jordan and Weiss: Probabilistic inference in graphical models 1 INTRODUCTION A " graphical model " is a type of probabilistic network that has roots in several different framework provides a clean mathematical formalism that has made it possible to understand the relationships among a wide variety of network-based approaches to computation, and in particular to understand many neural network algorithms and architectures as instances of a broader probabilistic methodology. Graphical models use… CONTINUE READING
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Learning in Graphical Models, Cambridge, MA: MIT Press

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