Algorithmic barriers to representing conditional independence.
Nathanael L. AckermanJeremy AvigadCameron E. FreerDaniel M. RoyJason M. RutePublished in: LICS (2019)
Keyphrases
- conditional independence
- bayesian networks
- random variables
- probability distribution
- learning bayesian networks
- graphical models
- structure learning
- bayesian network structure
- causal models
- directed acyclic graph
- statistical independence
- probability theory
- gaussian model
- axiomatic characterization
- structure and parameter learning
- causal independence
- chain graphs
- possibility theory
- markov blanket
- causal discovery
- conditional independencies
- machine learning
- markov property
- neural network
- graphical representation