Causal Discovery over High-Dimensional Structured Hypothesis Spaces with Causal Graph Partitioning.
Ashka ShahAdela DePaviaNathaniel HudsonIan T. FosterRick StevensPublished in: CoRR (2024)
Keyphrases
- causal discovery
- graph partitioning
- hypothesis spaces
- high dimensional
- causal models
- causal relationships
- causal structure
- hypothesis space
- discovery process
- inductive inference
- image segmentation
- bayesian networks
- graph model
- weighted graph
- clustering algorithm
- directed acyclic graph
- data clustering
- dimensionality reduction
- conditional independence
- observational data
- learning machines
- spectral clustering
- superpixels
- data points
- feature space
- data mining
- information retrieval
- pattern languages
- knowledge discovery
- data sets
- decision trees
- learning algorithm
- lower bound