Constraining Variational Inference with Geometric Jensen-Shannon Divergence.
Jacob DeasyNikola SimidjievskiPietro LiòPublished in: CoRR (2020)
Keyphrases
- jensen shannon divergence
- variational inference
- bayesian inference
- information theory
- information theoretic
- probabilistic graphical models
- topic models
- probabilistic model
- mixture model
- gaussian process
- variational methods
- latent dirichlet allocation
- posterior distribution
- feature selection
- closed form
- mutual information
- exponential family
- selection criterion
- exact inference
- graphical models
- factor graphs
- prior information
- unsupervised learning
- maximum likelihood
- learning algorithm
- approximate inference
- machine learning
- parameter estimation
- dimensionality reduction
- feature extraction