Fixing Variational Bayes: Deterministic Variational Inference for Bayesian Neural Networks.
Anqi WuSebastian NowozinEdward MeedsRichard E. TurnerJosé Miguel Hernández-LobatoAlexander L. GauntPublished in: CoRR (2018)
Keyphrases
- variational inference
- variational bayes
- bayesian inference
- neural network
- posterior distribution
- latent dirichlet allocation
- hyperparameters
- exponential family
- latent variables
- probabilistic model
- bayesian learning
- maximum likelihood
- topic models
- prior information
- markov chain monte carlo
- bayesian framework
- parameter estimation
- probability distribution
- posterior probability
- model selection
- maximum a posteriori
- text mining
- closed form
- gaussian distribution
- conditional random fields
- incomplete data
- missing data
- generative model
- free energy
- support vector