Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks.
Daiwei ZhangTianci LiuJian KangPublished in: CoRR (2022)
Keyphrases
- neural network
- decision theory
- sparse bayesian learning
- measurement errors
- measurement noise
- sensor noise
- dempster shafer
- gaussian processes
- belief nets
- random noise
- back propagation
- noise level
- missing data
- probability measure
- relevance vector machine
- measurement error
- bayesian approaches
- arbitrary shape
- bayesian networks
- pattern recognition
- uncertain data
- fuzzy logic
- maximum likelihood
- regression method
- feed forward
- noisy data
- artificial neural networks
- model selection
- fault diagnosis
- regression analysis
- bayesian inference
- multi layer
- self organizing maps
- signal to noise ratio
- noise reduction
- belief functions
- least squares
- median filter
- model averaging