GpABC: a Julia package for approximate Bayesian computation with Gaussian process emulation.
Evgeny TankhilevichJonathan Ish-HorowiczTara HameedElisabeth RoeschIstvan T. KleijnMichael P. H. StumpfFei HePublished in: Bioinform. (2020)
Keyphrases
- gaussian process
- expectation propagation
- gaussian processes
- marginal likelihood
- gaussian process classification
- hyperparameters
- gaussian process regression
- approximate inference
- model selection
- regression model
- bayesian inference
- fully bayesian
- bayesian framework
- gaussian process models
- posterior distribution
- bayesian methods
- density estimation
- latent variables
- semi supervised
- covariance function
- bayesian networks
- sparse approximations
- closed form
- sparse approximation
- data sets
- posterior probability
- human pose estimation
- graphical models
- probabilistic model
- support vector