% GP toolbox
% Version 0.137		22-Jul-2011
% Copyright (c) 2011, Neil D. Lawrence
% 
, Neil D. Lawrence
% GPSCALEBIASGRADIENT Compute the log likelihood gradient wrt the scales.
% GPCOMPUTEM Compute the matrix m given the model.
% DEMSPGP1DGP3 Do a simple 1-D regression after Snelson & Ghahramani's example.
% GPOBJECTIVEGRADIENT Wrapper function for GP objective and gradient.
% GPTOOLBOXES Load in the relevant toolboxes for GP.
% GPOPTIMISE Optimise the inducing variable based kernel.
% GPPOSTERIORVAR Variances of the posterior at points given by X.
% DEMSTICKGP1 Demonstrate Gaussian processes for regression on stick man data.
% GPUPDATEKERNELS Update the kernels that are needed.
% GPLOADRESULT Load a previously saved result.
% GPREADFROMFILE Load a file produced by the C++ implementation.
% DEMSILHOUETTEGP2 Model silhouette data with independent MLP GPs.
% GPGRADIENT Gradient wrapper for a GP model.
% DEMSPGP1DPLOT Plot results from 1-D sparse GP.
% GPDECONSTRUCT break GP in pieces for saving.
% DEMGPTWOSAMPLELIFSH Run GP two sample code on LifSh.
% GPOBJECTIVE Wrapper function for GP objective.
% GPMEANFUNCTIONGRADIENT Compute the log likelihood gradient wrt the scales.
% GPSUBSPACEEXPANDPARAM 
% GPSUBSPACECREATE 
% GPEXTRACTPARAM Extract a parameter vector from a GP model.
% DEMGPSAMPLE Simple demonstration of sampling from a covariance function.
% GPCOMPUTETRANSLATIONLOGLIKELIHOOD  
% DEMOPTIMISEGP Shows that there is an optimum for the covariance function length scale.
% DEMSILHOUETTELINEAR1 Model silhouette data with independent linear models.
% GPPOINTLOGLIKELIHOOD Log-likelihood of a test point for a GP.
% DEMOPTIMISEGPTUTORIAL Shows that there is an optimum for the covariance function length scale.
% DEMSPGP1DGP2 Do a simple 1-D regression after Snelson & Ghahramani's example.
% DEMINTERPOLATION Demonstrate Gaussian processes for interpolation.
% DEMSPGP1DGP4 Do a simple 1-D regression after Snelson & Ghahramani's example.
% DEMSPGP1DGP5 Do a simple 1-D regression after Snelson & Ghahramani's example.
% DEMGPCOVFUNCSAMPLE Sample from some different covariance functions.
% GPUPDATEAD Update the representations of A and D associated with the model.
% DEMSILHOUETTEPLOTTRUE Plot the true poses for the silhouette data.
% DEMSILHOUETTEPLOT
% GPCOMPUTEOBSERVATIONLOGLIKELIHOOD  
% GPEXPANDPARAM Expand a parameter vector into a GP model.
% GPSUBSPACEOUT
% GPDISPLAY Display a Gaussian process model.
% GPDATAINDICES Return indices of present data.
% GPPOSTERIORGRADMEANVAR Gadient of the mean and variances of the posterior at points given by X.
% GPPOSTERIORMEANVAR Mean and variances of the posterior at points given by X.
% DEMGPTWOSAMPLELIF Run GP two sample code on LIF.
% GPWRITERESULT Write a GP result.
% DEMGPCOV2D Simple demonstration of sampling from a covariance function.
% GPPOSTERIORSAMPLE Create a plot of samples from a posterior covariance.
% GPCOVGRADS Sparse objective function gradients wrt Covariance functions for inducing variables.
% GPLOGLIKEGRADIENTS Compute the gradients for the parameters and X.
% DEMSPGP1DGP1 Do a simple 1-D regression after Snelson & Ghahramani's example.
% DEMGPTWOSAMPLEEB Run GP two sample code on EB.
% GPOUT Evaluate the output of an Gaussian process model.
% GPBLOCKINDICES Return indices of given block.
% GPCOVGRADSTEST Test the gradients of the likelihood wrt the covariance.
% DEMGPTWOSAMPLE Test GP two sample code.
% GPTWOSAMPLE Do Oliver Stegles simple two sample test on a data set.
% GPSUBSPACEEXTRACTPARAM
% DEMSILHOUETTEGP1 Model silhouette data with independent RBF GPs.
% GPREADFROMFID Load from a FID produced by the C++ implementation.
% DEMREGRESSION Demonstrate Gaussian processes for regression.
% GPCREATE Create a GP model with inducing varibles/pseudo-inputs.
% GPCOMPUTEALPHA Update the vector `alpha' for computing posterior mean quickly.
% GPLOGLIKELIHOOD Compute the log likelihood of a GP.
% GPPOSTERIORGRADMEANCOVAR Gadient of the mean and variances of the posterior at points given by X.
% GPTEST Test the gradients of the gpCovGrads function and the gp models.
% GPWRITETOFILE Write a file to be read by the C++ implementation.
% GPSAMPLE Create a plot of samples from a GP.
% GPRECONSTRUCT Reconstruct an GP form component parts.
% GPPOSTERIORMEANCOVAR Mean and covariances of the posterior at points given by X.
% GPPOSTERIORMEANCOVARTEST Test the gradients of the mean and covariance.
% DEMSILHOUETTEAVERAGE Shows the average of the poses.
% GPSUBSPACEOPTIMISE
% GPOPTIONS Return default options for GP model.
