BayesDAG: Gradient-Based Posterior Inference for Causal Discovery.
Yashas AnnadaniNick PawlowskiJoel JenningsStefan BauerCheng ZhangWenbo GongPublished in: NeurIPS (2023)
Keyphrases
- causal discovery
- bayesian networks
- causal models
- causal relationships
- posterior probability
- discovery process
- causal structure
- observational data
- probability distribution
- probabilistic model
- markov blanket
- probabilistic inference
- directed acyclic graph
- conditional independence
- bayesian inference
- gaussian process
- markov chain monte carlo
- graphical models
- parameter learning
- machine learning
- decision making
- belief networks
- dynamic programming