Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon.
Jeremiah Zhe LiuPublished in: CoRR (2019)
Keyphrases
- variable selection
- neural network
- von mises
- posterior distribution
- posterior probability
- cross validation
- gaussian distribution
- input variables
- hyperparameters
- model selection
- probability density function
- high dimensional
- conditional probabilities
- dimension reduction
- bayesian framework
- probability distribution
- pattern recognition
- bayesian networks
- prior distribution
- parameter estimation
- artificial neural networks
- probabilistic model
- latent variables
- gaussian process
- fuzzy logic
- heavy tailed
- feature selection
- gaussian processes
- neural network model
- high dimensional data
- maximum likelihood
- face recognition
- training set
- maximum a posteriori
- principal component analysis
- nearest neighbor
- computer vision