Improving Bayesian Inference in Deep Neural Networks with Variational Structured Dropout.
Son NguyenDuong NguyenKhai NguyenNhat HoKhoat ThanHung BuiPublished in: CoRR (2021)
Keyphrases
- bayesian inference
- neural network
- probabilistic model
- prior information
- hyperparameters
- variational approximation
- image segmentation
- gibbs sampler
- bayesian model
- statistical inference
- variational inference
- weighted model counting
- hidden variables
- hierarchical bayesian
- markov networks
- posterior distribution
- probabilistic modeling
- neural network model
- variational bayes
- back propagation
- support vector
- markov chain monte carlo
- bayesian models
- conditional random fields