High-Dimensional Inference for Cluster-Based Graphical Models.
Carson EisenachFlorentina BuneaYang NingClaudiu DinicuPublished in: J. Mach. Learn. Res. (2020)
Keyphrases
- graphical models
- high dimensional
- probabilistic inference
- exact inference
- map inference
- undirected graphical models
- belief propagation
- belief networks
- bayesian networks
- factor graphs
- probabilistic model
- approximate inference
- loopy belief propagation
- efficient inference algorithms
- statistical inference
- probabilistic graphical models
- nonparametric belief propagation
- random variables
- directed graphical models
- markov networks
- structure learning
- markov logic networks
- relational dependency networks
- collective classification
- conditional random fields
- possibilistic networks
- conditional independence
- statistical relational learning
- probabilistic networks
- marginal probabilities
- dynamic bayesian networks
- bayesian inference
- exponential family
- probabilistic reasoning
- structured prediction
- partition function
- junction tree
- inference process
- message passing
- gene expression data
- feature space