About: The GPstuff toolbox is a versatile collection of Gaussian process models and computational tools required for inference. The tools include, among others, various inference methods, sparse approximations and model assessment methods.

2016-06-09 Version 4.7

Development and release branches available at https://github.com/gpstuff-dev/gpstuff

New features

• Simple Bayesian Optimization demo

Improvements

• Improved use of PSIS
• More options added to gp_monotonic
• Monotonicity now works for additive covariance functions with selected variables
• Possibility to use gpcf_squared.m-covariance function with derivative observations/monotonicity
• Default behaviour made more robust by changing default jitter from 1e-9 to 1e-6
• LA-LOO uses the cavity method as the default (see Vehtari et al (2016). Bayesian leave-one-out cross-validation approximations for Gaussian latent variable models. JMLR, accpeted for publication)
• Selected variables -option works now better with monotonicity

Bugfixes

• small error in derivative observation computation fixed
• several minor bug fixes