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Gaussian Process Derivative at Uncertain Input for SE Kernel
Full text linkGiven a Gaussian Process with a zero mean and a Squared Exponential (SE) kernel. We are interested in the exact mean and covariance of the predictive distribution of the latent function f and its gradient ∂f/∂x at an uncertain input x ∼ N(μ,Σ). This technical note develops the calculations of these quantities and documents an implementation of these calculations in a Matlab function called gppred_exactmoments_se
The data behind article "Laser Irradiation of Carbonaceous Chondrite Simulants: Space Weathering Implications for C-complex Asteroids"
No full textThe data shown in Figures 1-7 are available in the .zip file. Each Figure has one or more text files containing tab delimited tabular data. The readme file gives more details of the contents for each Figure
