GibbsNet: Iterative Adversarial Inference for Deep Graphical Models.
Alex LambR. Devon HjelmYaroslav GaninJoseph Paul CohenAaron C. CourvilleYoshua BengioPublished in: CoRR (2017)
Keyphrases
- graphical models
- probabilistic inference
- exact inference
- map inference
- bayesian networks
- belief networks
- belief propagation
- loopy belief propagation
- probabilistic model
- factor graphs
- undirected graphical models
- approximate inference
- efficient inference algorithms
- nonparametric belief propagation
- probabilistic graphical models
- random variables
- statistical inference
- probabilistic networks
- relational dependency networks
- directed graphical models
- conditional random fields
- markov networks
- possibilistic networks
- graphical structure
- collective classification
- probabilistic reasoning
- graph structure
- statistical relational learning
- generalized belief propagation
- structure learning
- conditional independence
- multi agent
- marginal probabilities
- markov logic networks
- bayesian belief networks
- bayesian inference
- junction tree
- chain graphs
- parameter learning
- free energy
- inference process
- exponential family
- random fields
- conditional probabilities
- dynamic bayesian networks