Probabilistic Circuits for Variational Inference in Discrete Graphical Models.
Andy ShihStefano ErmonPublished in: NeurIPS (2020)
Keyphrases
- graphical models
- variational inference
- probabilistic model
- factor graphs
- probabilistic graphical models
- exact inference
- approximate inference
- bayesian inference
- belief propagation
- bayesian networks
- belief networks
- random variables
- markov networks
- probabilistic inference
- generative model
- exponential family
- conditional random fields
- mixture model
- variational methods
- structure learning
- latent variables
- conditional probabilities
- topic models
- conditional independence
- message passing
- posterior probability
- expectation maximization
- support vector
- first order logic
- probability distribution
- co occurrence
- dynamic bayesian networks
- gaussian process
- posterior distribution