ndlutil toolbox and the optimi toolbox. You can use your username and password for accessing these toolboxes.
Current release is 0.163.
This release removes the stubs for several KernDiagGradX.m files, which were confusing kernDiagGradX.m, which assumes they only exist if the function is implemented. For the kernel types 'lin', 'poly', 'mlp', and their 'ard' counter-types, these files existed but weren't yet implemented.
Release 0.162 implements some Matern kernels, the rational quadratic and Mark Gibbs's non-stationary kernel.
Release 0.161 introduced the single input motif kernel for the GPSIM toolbox. Also there is much more documentation, and a new file kernelGenerator.py for creating the basic files for your own kernels.
This toolbox allows computation of several different kernels and their gradients. You can add kernels to the toolbox by creating versions of the relevant files. Once added, they can be tested using the kernTest. For example you can test the RBF kernel by writing
>> kernTest('rbf')
There are several kernels implemented, the ones that are being maintained for the latest release are:
lin
linard
rbf
rbfard
mlp
mlpard
poly
polyard
white
whitefixed
bias
cmpnd
tensor (tensor kernels).
file (a kernel written in a file).
A new kernel can be created using the compound kernel, cmpnd. The compound kernel is made up of sums of individual kernels. Most often you will need to create a kernel containing a base kernel (e.g. rbf) and adding a white noise kernel, white and perhaps a constant offset through the bias kernel bias. On initialisation most kernel parameters are set to 1. Exceptions are ARD scale parameters, and the variance of the white and bias kernels.