Particle MCMC algorithms and architectures for accelerating inference in state-space models.
Grigorios MingasLeonardo BottoloChristos-Savvas BouganisPublished in: Int. J. Approx. Reason. (2017)
Keyphrases
- markov chain monte carlo
- state space
- posterior distribution
- gibbs sampler
- markov chain
- linear gaussian
- monte carlo
- probabilistic model
- gibbs sampling
- data structure
- bayesian inference
- particle filter
- parameter estimation
- learning algorithm
- prior knowledge
- learning models
- mathematical models
- machine learning algorithms
- bayesian framework
- dynamic programming
- computational complexity
- bayesian networks