Use of Prior Knowledge to Discover Causal Additive Models with Unobserved Variables and its Application to Time Series Data.
Takashi Nicholas MaedaShohei ShimizuPublished in: CoRR (2024)
Keyphrases
- additive models
- causal effects
- prior knowledge
- linear models
- observational data
- causal relationships
- latent variables
- causal relations
- observed variables
- causal models
- variable selection
- hidden variables
- high dimensional
- causal discovery
- directed acyclic graph
- bayesian networks
- prior information
- machine learning
- generative model
- cross validation
- sample size