Graphical model inference: Sequential Monte Carlo meets deterministic approximations.
Fredrik LindstenJouni HelskeMatti ViholaPublished in: CoRR (2019)
Keyphrases
- graphical models
- sequential monte carlo
- probabilistic inference
- exact inference
- nonparametric belief propagation
- particle filter
- partition function
- map inference
- approximate inference
- undirected graphical models
- factor graphs
- belief networks
- belief propagation
- importance sampling
- bayesian networks
- efficient inference algorithms
- probabilistic model
- random variables
- visual tracking
- probabilistic graphical models
- variational methods
- conditional random fields
- posterior distribution
- directed graphical models
- models with hidden variables
- message passing
- bayesian inference
- structured prediction
- markov chain monte carlo
- dynamic bayesian networks
- markov networks
- particle filtering
- prior knowledge
- appearance model
- multiple objects
- closed form
- monte carlo