Ordering-Based Causal Structure Learning in the Presence of Latent Variables.
Daniel Irving BernsteinBasil SaeedChandler SquiresCaroline UhlerPublished in: AISTATS (2020)
Keyphrases
- latent variables
- structure learning
- bayesian networks
- probabilistic model
- graphical models
- random variables
- causal relationships
- conditional independence
- observed variables
- hidden variables
- gaussian process
- posterior distribution
- parameter learning
- prior knowledge
- causal discovery
- markov networks
- markov logic networks
- probabilistic graphical models
- approximate inference
- generative model
- topic models
- transfer learning
- posterior probability
- parameter estimation
- conditional random fields
- probabilistic inference
- causal models
- belief propagation
- dependency structure
- sample size
- exact inference
- structured prediction
- probability distribution
- conditional probabilities
- network structure
- directed acyclic graph
- max margin
- bayesian inference
- information retrieval