High-recall causal discovery for autocorrelated time series with latent confounders.
Andreas GerhardusJakob RungePublished in: NeurIPS (2020)
Keyphrases
- high recall
- causal discovery
- observational data
- high precision
- causal models
- causal relationships
- latent variables
- causal structure
- precision and recall
- bayesian networks
- directed acyclic graph
- discovery process
- conditional independence
- experimental data
- information extraction
- markov blanket
- databases
- decision makers
- exact match
- state space
- data mining
- high dimensional
- markov chain
- database
- random variables