Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?
Chaoqi WangShengyang SunRoger B. GrossePublished in: AISTATS (2021)
Keyphrases
- regression model
- gaussian process
- gaussian processes
- posterior distribution
- multivariate regression
- posterior probability
- probability distribution
- conditional distribution
- response variable
- decision theory
- regression analysis
- regression methods
- model selection
- markov chain monte carlo methods
- prediction model
- conditional probabilities
- bayesian networks
- maximum likelihood
- generalized linear models
- regression trees
- linear model
- approximate inference
- confidence intervals
- interval valued data
- multiple linear regression
- explanatory variables
- neural network
- linear regression model
- predictive model
- marginal distributions
- target variable
- feature selection
- independent variables
- machine learning
- markov chain monte carlo
- data mining
- bayesian framework
- bayesian inference