Functional regression approximate Bayesian computation for Gaussian process density estimation.
G. S. RodriguesDavid J. NottScott A. SissonPublished in: Comput. Stat. Data Anal. (2016)
Keyphrases
- expectation propagation
- density estimation
- gaussian process
- gaussian processes
- regression model
- reproducing kernel hilbert space
- gaussian process regression
- model selection
- covariance function
- mixture model
- approximate inference
- probability density function
- latent variables
- bayesian inference
- bayesian framework
- hyperparameters
- outlier detection
- density function
- bayesian methods
- gaussian mixture model
- feature selection
- semi supervised
- posterior distribution
- em algorithm
- exponential family
- computer vision
- data sets
- closed form