Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data.
Dominik LinznerMichael SchmidtHeinz KoepplPublished in: NeurIPS (2019)
Keyphrases
- structure learning
- incomplete data
- bayesian networks
- learning bayesian networks
- graphical models
- conditional independence
- parameter learning
- missing data
- probability distribution
- missing values
- parameter estimation
- probabilistic inference
- dynamic bayesian networks
- markov networks
- hyperparameters
- em algorithm
- transfer learning
- hidden variables
- probabilistic model
- probabilistic graphical models
- higher order
- conditional random fields
- sample size
- random variables
- input data
- feature selection