Sparse Bayesian neural networks for regression: Tackling overfitting and computational challenges in uncertainty quantification.
Nastaran DabiranBrandon RobinsonRimple SandhuMohammad KhalilDominique PoirelAbhijit SarkarPublished in: CoRR (2023)
Keyphrases
- computational challenges
- neural network
- relevance vector machine
- huge number
- pattern recognition
- regression model
- cross validation
- artificial neural networks
- fuzzy logic
- model selection
- recurrent neural networks
- automatic relevance determination
- regression problems
- uncertain data
- back propagation
- genetic algorithm
- nonlinear regression
- regression algorithm
- linear regression
- decision trees
- multi task
- real world
- radial basis function network
- partial least squares
- decision theory
- regression analysis
- gaussian processes
- support vector regression
- support vector machine
- feed forward
- neural network model
- multi layer
- neural nets
- activation function
- feature selection
- rough sets
- multilayer perceptron
- simple linear
- radial basis function
- machine learning
- fault diagnosis