Efficient Priors for Scalable Variational Inference in Bayesian Deep Neural Networks.
Ranganath KrishnanMahesh SubedarOmesh TickooPublished in: ICCV Workshops (2019)
Keyphrases
- variational inference
- neural network
- bayesian models
- bayesian inference
- posterior distribution
- probabilistic model
- posterior probability
- mixture model
- gaussian process
- dirichlet process
- closed form
- bayesian framework
- topic models
- gaussian processes
- variational methods
- bayesian networks
- prior information
- hyperparameters
- expectation maximization
- probabilistic graphical models
- maximum likelihood