Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning.
Veit D. WildRobert HuDino SejdinovicPublished in: NeurIPS (2022)
Keyphrases
- deep learning
- variational inference
- bayesian inference
- posterior distribution
- probabilistic graphical models
- topic models
- unsupervised learning
- maximum likelihood
- closed form
- mixture model
- probabilistic model
- gaussian process
- parameter estimation
- variational methods
- latent variables
- machine learning
- latent dirichlet allocation
- exponential family
- mental models
- probability distribution
- gaussian distribution
- approximate inference
- hyperparameters
- posterior probability
- bayesian framework
- bayesian networks