Discrete Latent Variables Discovery and Structure Learning in Mixed Bayesian Networks.
Aviv PeledShai FinePublished in: ICMLA (2021)
Keyphrases
- structure learning
- latent variables
- bayesian networks
- probabilistic model
- random variables
- continuous variables
- graphical models
- conditional independence
- parameter learning
- approximate inference
- causal discovery
- posterior distribution
- hidden variables
- observed variables
- probability distribution
- exact inference
- parameter estimation
- factor graphs
- probabilistic graphical models
- topic models
- gaussian process
- structure learning algorithm
- markov networks
- probabilistic inference
- dynamic bayesian networks
- transfer learning
- continuous domains
- generative model
- information retrieval
- dependency structure
- prior knowledge
- max margin
- data mining
- conditional random fields
- structured prediction
- belief propagation
- posterior probability
- sample size
- belief networks