Itô-SDE MCMC method for Bayesian characterization of errors associated with data limitations in stochastic expansion methods for uncertainty quantification.
Maarten ArnstB. Abello ÁlvarezJ.-P. PonthotRomain BomanPublished in: J. Comput. Phys. (2017)
Keyphrases
- statistical methods
- hybrid method
- synthetic data
- computational cost
- noisy data
- classification method
- bayesian methods
- significant improvement
- monte carlo method
- input data
- high dimensional data
- data sets
- missing values
- machine learning methods
- preprocessing
- spectral clustering
- cross validation
- incomplete data
- statistical significance
- markov chain
- bayesian inference
- predictive model
- monte carlo
- missing data
- clustering method
- large scale data sets
- data mining techniques
- prior knowledge
- methods require
- uncertain data
- bayesian models
- prior distribution
- pairwise
- data analysis
- sampling methods
- chronological backtracking
- receiver operating characteristic curves
- markov chain monte carlo
- posterior distribution
- prior information
- model selection
- probability distribution
- data sources
- training data
- image segmentation