Mixture of noises and sampling of non-log-concave posterior distributions.
Pierre PaludPierre ChainaisFranck Le PetitEmeric BronPierre-Antoine ThouveninMaxime VonoL. EinigM. Garcia Santa-MariaMathilde GaudelJan H. OrkiszVictor de Souza MagalhaesSébastien BardeauMaryvonne GerinJavier R. GoicoecheaPierre GratierViviana V. GuzmánJouni KainulainenFrançois LevrierNicolas PerettoJérome PetyAntoine RoueffAlbrecht SieversPublished in: EUSIPCO (2022)
Keyphrases
- posterior distribution
- metropolis hastings
- markov chain monte carlo
- gaussian distribution
- dirichlet process
- sequential monte carlo
- hyperparameters
- expectation maximization
- probability distribution
- random sampling
- parameter estimation
- prior distribution
- latent variables
- exponential family
- sampling algorithm
- bayesian framework
- posterior probability
- mixture model
- maximum a posteriori
- variational inference
- particle filtering
- sample size
- gaussian mixture model
- generative model
- model selection
- training data
- machine learning
- active learning
- probabilistic model
- maximum likelihood
- em algorithm
- gaussian process
- monte carlo