Graphical Models for Probabilistic Reasoning

Graphical Models for Probabilistic Reasoning

• Bayesian networks
  • Model for causal and/or correlational influences
  • Directed graph encodes dependency relationships
  • Local probability distributions encode strength of relationships
• Markov networks
  • Model for correlational influences
  • Undirected graph encodes dependency relationships
  • Local probability distributions encode strength of relationships
• Hybrids and extensions
• Other models that can be viewed as graphical probability models
  • Neural networks
  • Networks of rules with certainty factors

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