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main.m
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%% Explainable Learning with Gaussian Processes
% This code reproduces the figures from our paper. To generate all figures
% (as .png files), you just need to run main.m. The code should run with no
% issues using Matlab 2022a or later. All generated figures and tables will
% be saved to the results folder.
%% Set up the Matlab path
addpath(genpath('./data'))
addpath('./functions')
addpath('./results')
addpath('./scripts')
%% Experiments
% Running these scripts will reproduce experiments from the paper
% Heteroscedasticity of the attribution GPs
% (Fig. 1 of the paper)
exp3_heteroscedastic
% Breast Cancer Prognostic data
% (Fig. 2 of the paper)
exp1_general
% Taipei housing data figure
% (Fig. 3 in the paper)
exp2_taipei
% Numerical integration comparison
% (Fig. 4 of the paper)
exp4_quadrature
% RFGP sparse approximation comparison
% (Fig. 5 of the paper)
exp5_rfgps
% Appendix plots
% Quadrature rule figures
suppl_quadrature