Using multi-step proposal distribution for improved MCMC convergence in Bayesian network structure learning.
Antti LarjoHarri LähdesmäkiPublished in: EURASIP J. Bioinform. Syst. Biol. (2015)
Keyphrases
- multi step
- proposal distribution
- particle filter
- bayesian network structure learning
- particle filtering
- posterior distribution
- markov chain monte carlo
- feature tracking
- metropolis hastings algorithm
- graph theoretic
- importance sampling
- density function
- object tracking
- bayesian networks
- simultaneous localization and mapping
- convergence rate
- markov chain
- mean shift
- motion model
- observation model
- visual tracking
- knn
- data association
- probability distribution
- latent variables
- appearance model
- kalman filter
- monte carlo
- k nearest neighbor
- markov random field
- state space
- search algorithm