Training Bayesian Neural Networks with Sparse Subspace Variational Inference.
Junbo LiZichen MiaoQiang QiuRuqi ZhangPublished in: ICLR (2024)
Keyphrases
- variational inference
- neural network
- bayesian inference
- posterior distribution
- topic models
- gaussian process
- probabilistic model
- mixture model
- latent dirichlet allocation
- high dimensional
- closed form
- variational methods
- probability distribution
- probabilistic graphical models
- exponential family
- latent variables
- approximate inference
- factor graphs
- hyperparameters
- supervised learning
- graphical models
- maximum a posteriori
- prior information
- exact inference
- parameter estimation
- gaussian processes
- bayesian networks
- generative model
- principal component analysis
- dimensionality reduction
- low dimensional
- high dimensional data
- maximum likelihood