On the choice of MCMC kernels for approximate Bayesian computation with SMC samplers.
Anthony LeePublished in: WSC (2012)
Keyphrases
- markov chain monte carlo
- exact computation
- bayesian inference
- posterior distribution
- posterior probability
- markov chain
- generative model
- approximate inference
- parameter estimation
- expectation propagation
- monte carlo
- sampling algorithm
- particle filter
- bayesian learning
- kernel function
- gibbs sampler
- weighted sums
- graphical models
- bayesian networks
- efficient computation
- simulated annealing
- probability distribution
- numerical integration
- latent variables
- gaussian processes
- feature space
- random sampling
- bayesian framework
- model selection
- maximum likelihood
- multiple kernel
- neural network