Parameter Priors for Directed Acyclic Graphical Models and the Characterization of Several Probability Distributions.
Dan GeigerDavid HeckermanPublished in: CoRR (2021)
Keyphrases
- directed acyclic
- graphical models
- random variables
- probability distribution
- bayesian networks
- belief propagation
- graph structure
- probabilistic graphical models
- probabilistic inference
- probabilistic model
- structure learning
- conditional independence
- belief networks
- approximate inference
- exact inference
- markov networks
- conditional random fields
- conditional probabilities
- undirected graphical models
- latent variables
- posterior distribution
- structural learning
- chain graphs
- joint distribution
- bayesian framework
- prior information
- factor graphs
- random walk
- statistical models
- marginal distributions