Understanding Approximation for Bayesian Inference in Neural Networks.
Sebastian FarquharPublished in: CoRR (2022)
Keyphrases
- bayesian inference
- neural network
- expectation propagation
- probabilistic model
- variational approximation
- prior information
- hyperparameters
- variational inference
- variational bayes
- bayesian model
- artificial neural networks
- statistical inference
- neural network model
- hierarchical bayesian
- hidden variables
- data sets
- bayesian models
- gaussian process
- training data
- probabilistic modeling
- machine learning
- gibbs sampler
- competitive learning
- prior distribution
- approximation algorithms
- back propagation
- generative model
- state space
- pairwise