Graphical model inference: Sequential Monte Carlo meets deterministic approximations.
Fredrik LindstenJouni HelskeMatti ViholaPublished in: NeurIPS (2018)
Keyphrases
- graphical models
- sequential monte carlo
- nonparametric belief propagation
- particle filter
- probabilistic inference
- exact inference
- map inference
- approximate inference
- belief networks
- bayesian networks
- factor graphs
- belief propagation
- partition function
- importance sampling
- efficient inference algorithms
- undirected graphical models
- probabilistic model
- visual tracking
- particle filtering
- probabilistic graphical models
- random variables
- variational methods
- directed graphical models
- markov networks
- bayesian inference
- dynamic bayesian networks
- conditional random fields
- object tracking
- models with hidden variables
- message passing
- structured prediction
- markov chain monte carlo
- articulated body
- closed form
- appearance model
- mean shift
- data association
- kalman filter
- pose estimation
- video sequences