Discovery of Causal Models that Contain Latent Variables Through Bayesian Scoring of Independence Constraints.
Fattaneh JabbariJoseph D. RamseyPeter SpirtesGregory F. CooperPublished in: ECML/PKDD (2) (2017)
Keyphrases
- latent variables
- causal models
- observational data
- causal discovery
- posterior distribution
- observed variables
- conditional independence
- causal relationships
- observable variables
- structural model
- conditional independencies
- probabilistic model
- random variables
- bayesian networks
- variational approximation
- hidden variables
- causal structure
- prior knowledge
- bayesian learning
- latent variable models
- directed acyclic graph
- gaussian process
- topic models
- variational bayes
- approximate inference
- causal relations
- structural svms
- experimental data
- graphical models
- causal reasoning
- maximum likelihood
- causal effects
- structural equation models
- bayesian inference
- max margin
- markov chain monte carlo
- structure learning
- knowledge discovery
- data sets
- gaussian processes
- generative model
- tractable cases
- posterior probability