Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature.
Tom GunterMichael A. OsborneRoman GarnettPhilipp HennigStephen J. RobertsPublished in: NIPS (2014)
Keyphrases
- probabilistic model
- bayesian inference
- gibbs sampler
- markov chain monte carlo
- bayesian networks
- generative model
- variational inference
- posterior probability
- posterior distribution
- graphical models
- bayesian model
- latent variables
- bayesian models
- probabilistic modeling
- statistical inference
- inference process
- metropolis hastings
- hidden variables
- hyperparameters
- language model
- expectation maximization
- random fields
- variational approximation
- exact inference
- sampling strategy
- gibbs sampling
- sampling algorithm
- rotation invariant
- random sampling
- probabilistic inference
- mixture model
- sampling methods
- sequential monte carlo
- conditional random fields
- bayesian learning
- fourier transform
- bayesian model selection
- amplitude modulation
- band limited
- dirichlet process
- prior information
- loopy belief propagation
- bayesian framework
- topic models
- conditional probabilities
- probabilistic graphical models
- particle filter
- approximate inference
- markov chain
- markov networks