Inference in Probabilistic Graphical Models by Graph Neural Networks.
KiJung YoonRenjie LiaoYuwen XiongLisa ZhangEthan FetayaRaquel UrtasunRichard S. ZemelXaq PitkowPublished in: CoRR (2018)
Keyphrases
- probabilistic graphical models
- exact inference
- markov logic
- neural network
- graphical models
- probabilistic inference
- parameter learning
- markov logic networks
- markov networks
- approximate inference
- bayesian networks
- first order logic
- belief propagation
- belief networks
- structured prediction
- conditional random fields
- back propagation
- dynamic bayesian networks
- random variables
- fuzzy logic
- soft computing
- artificial neural networks
- structure learning
- latent variables
- directed acyclic graph
- knowledge representation
- pattern recognition
- message passing
- approximation algorithms
- regression model
- text mining
- least squares
- fuzzy measures
- genetic algorithm
- machine learning