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.
Changes:
2016-06-09 Version 4.7
Development and release branches available at https://github.com/gpstuff-dev/gpstuff
New features
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Simple Bayesian Optimization demo
Improvements
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Improved use of PSIS
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More options added to gp_monotonic
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Monotonicity now works for additive covariance functions with selected
variables
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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
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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
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