PriorCVAE: scalable MCMC parameter inference with Bayesian deep generative modelling.
Elizaveta SemenovaMax Cairney-LeemingSeth R. FlaxmanPublished in: CoRR (2023)
Keyphrases
- markov chain monte carlo
- generative model
- bayesian inference
- posterior distribution
- posterior probability
- belief nets
- gibbs sampler
- gibbs sampling
- bayesian model
- probabilistic model
- parameter estimation
- bayesian networks
- sampling algorithm
- bayesian model selection
- data driven
- markov chain
- variational bayes
- monte carlo
- variational inference
- expectation propagation
- hyperparameters
- dirichlet process
- discriminative learning
- approximate inference
- bayesian framework
- mixture model
- inference process
- probability distribution
- variational approximation
- conjugate priors
- metropolis hastings algorithm
- parameter values
- semi supervised
- web scale
- latent variables
- conditional random fields
- exact inference
- markov logic networks
- bayesian learning
- maximum likelihood
- markov logic
- particle filter
- probabilistic inference
- parameter settings
- model selection
- metropolis hastings
- parameter space