Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models.
Adarsh K. JeewajeeLeslie Pack KaelblingPublished in: NeurIPS (2020)
Keyphrases
- undirected graphical models
- graphical models
- conditional random fields
- exact inference
- boltzmann machines
- probabilistic graphical models
- partition function
- approximate inference
- gene regulatory networks
- factor graphs
- probabilistic model
- structure learning
- markov random field
- markov networks
- belief propagation
- directed graphical models
- belief networks
- probabilistic inference
- posterior distribution
- bayesian networks
- neural network
- random variables
- structured prediction
- hidden variables
- graph structure
- undirected graph
- machine learning
- random fields
- message passing
- latent variables
- loopy belief propagation
- high dimensional
- bayesian inference
- boltzmann machine
- efficient learning
- importance sampling
- probability distribution
- learning algorithm