Modelling and inference with Conditional Gaussian Probabilistic Decision Graphs.
Jens Dalgaard NielsenJosé A. GámezAntonio SalmerónPublished in: Int. J. Approx. Reason. (2012)
Keyphrases
- graphical structure
- probabilistic networks
- random field model
- bayesian networks
- belief networks
- inference process
- conditional probabilities
- directed graphical models
- random fields
- probabilistic inference
- influence diagrams
- probabilistic reasoning
- graphical models
- probabilistic model
- bayesian reasoning
- logical inference
- decision theory
- decision makers
- mixture distributions
- probabilistic logic
- bayesian inference
- decision theoretic
- decision making
- latent variable models
- graph matching
- nonmonotonic inference
- directed graph
- maximum likelihood
- factor graphs
- graph theory
- conditionally independent
- bayes nets
- generative model
- decision problems
- continuous valued
- conditional probability distributions
- decision rules
- variable elimination
- markov logic networks
- belief propagation
- exact inference
- marginal distributions
- conditional independence
- probabilistic logic programs