Inference in probabilistic graphical models by Graph Neural Networks.
KiJung YoonRenjie LiaoYuwen XiongLisa ZhangEthan FetayaRaquel UrtasunRichard S. ZemelXaq PitkowPublished in: ICLR (Workshop) (2018)
Keyphrases
- probabilistic graphical models
- neural network
- markov logic
- exact inference
- graphical models
- probabilistic inference
- parameter learning
- markov logic networks
- markov networks
- bayesian networks
- approximate inference
- pattern recognition
- first order logic
- latent variables
- bayesian inference
- belief networks
- structured prediction
- soft computing
- belief propagation
- fuzzy logic
- conditional random fields
- multilayer perceptron
- random variables
- structure learning
- probabilistic model
- artificial neural networks
- approximation algorithms
- random fields
- belief functions
- generative model
- markov random field
- higher order
- fuzzy measures
- genetic algorithm