Layerwise Approximate Inference for Bayesian Uncertainty Estimates on Deep Neural Networks.
Ni ZhangXiaoyi ChenLi QuanPublished in: IJCNN (2021)
Keyphrases
- approximate inference
- neural network
- bayesian networks
- graphical models
- variational approximation
- probabilistic inference
- exact inference
- markov chain monte carlo
- belief propagation
- expectation propagation
- gaussian process
- parameter estimation
- conditional probabilities
- message passing
- latent variables
- conditional random fields
- variational methods
- loopy belief propagation
- dynamic bayesian networks
- variational inference
- factor graphs
- posterior probability
- probabilistic model
- posterior distribution
- structured prediction
- linear gaussian
- maximum likelihood
- random variables
- competitive learning
- back propagation
- free energy
- bayesian inference
- artificial neural networks
- multilayer perceptron
- pairwise
- support vector
- bayesian framework