Probabilistic Variational Bounds for Graphical Models.
Qiang LiuJohn W. Fisher IIIAlexander T. IhlerPublished in: NIPS (2015)
Keyphrases
- graphical models
- probabilistic model
- bayesian networks
- belief networks
- belief propagation
- factor graphs
- random variables
- approximate inference
- probabilistic inference
- conditional random fields
- probabilistic networks
- probabilistic graphical models
- markov networks
- generative model
- exact inference
- variational methods
- probabilistic reasoning
- conditional independence
- map inference
- upper bound
- structure learning
- directed graphical models
- marginal probabilities
- lower bound
- conditional probabilities
- bayesian inference
- optical flow
- nonparametric belief propagation
- image segmentation
- statistical relational learning
- lower and upper bounds
- message passing
- posterior probability
- markov logic networks
- probabilistic logic
- exponential family
- relational models
- latent variables
- maximum likelihood
- expectation maximization