WiseR: An end-to-end structure learning and deployment framework for causal graphical models.
Shubham MaheshwariKhushbu PahwaTavpritesh SethiPublished in: CoRR (2021)
Keyphrases
- graphical models
- structure learning
- end to end
- bayesian networks
- probabilistic model
- conditional independence
- markov blanket
- belief propagation
- random variables
- markov networks
- probabilistic inference
- probabilistic graphical models
- parameter learning
- markov logic networks
- dynamic bayesian networks
- approximate inference
- belief networks
- conditional random fields
- exact inference
- training data
- latent variables
- undirected graphical models
- possibilistic networks
- transfer learning
- probability distribution
- active learning
- statistical relational learning
- factor graphs
- optical flow