In many applications, we find that the prior mean is always set to zero as it is simple, convenient and works well for many applications. However, choosing the appropriate kernels for the task is not always straightforward. As mentioned in the previous section, kernels effectively try to map the similarity between two input data points in the input space to the output (function) space. The only requirement for the kernel function () is that it should map any two input values and to a scalar such that Kernel Matrix ( ...
Choosing kernels in GPs
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