Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification.
Gianni FranchiAndrei BursucEmanuel AldeaSéverine DubuissonIsabelle BlochPublished in: CoRR (2020)
Keyphrases
- neural network
- posterior distribution
- latent variables
- posterior probability
- decision theory
- bayesian learning
- conditional probabilities
- pattern recognition
- dempster shafer
- probability distribution
- artificial neural networks
- probabilistic model
- fuzzy logic
- bayesian estimation
- bayesian networks
- markov chain monte carlo
- competitive learning
- bayesian framework
- gaussian process
- model averaging
- uncertain data
- multilayer perceptron
- neural network model
- prior knowledge
- recurrent neural networks
- fuzzy systems
- belief functions
- bayesian methods
- back propagation
- particle filter
- genetic algorithm
- proposal distribution
- data driven
- maximum likelihood
- expected utility
- random variables
- gaussian processes
- feed forward