Walsh-Hadamard Variational Inference for Bayesian Deep Learning.
Simone RossiSébastien MarminMaurizio FilipponePublished in: NeurIPS (2020)
Keyphrases
- deep learning
- variational inference
- walsh hadamard
- bayesian inference
- posterior distribution
- probabilistic model
- mixture model
- unsupervised learning
- variational methods
- topic models
- gaussian process
- latent dirichlet allocation
- image matching
- probabilistic graphical models
- machine learning
- latent variables
- exact inference
- closed form
- exponential family
- probability distribution
- posterior probability
- hyperparameters
- approximate inference
- mental models
- markov chain monte carlo
- bayesian framework
- graphical models
- prior information
- bayesian networks
- model selection
- matching algorithm
- maximum a posteriori
- parameter estimation
- probabilistic inference
- feature extraction
- image processing