Sequential Monte Carlo for Graphical Models.
Christian A. NaessethFredrik LindstenThomas B. SchönPublished in: NIPS (2014)
Keyphrases
- graphical models
- sequential monte carlo
- probabilistic model
- belief propagation
- particle filter
- visual tracking
- approximate inference
- random variables
- probabilistic inference
- bayesian networks
- markov networks
- conditional random fields
- particle filtering
- importance sampling
- posterior distribution
- belief networks
- message passing
- latent variables
- probability distribution
- hidden markov models
- machine learning
- distributed systems
- lower bound
- higher order