penkovsky
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| """ | |
| The kernel function computes covariance between points using the RBF formula. | |
| The posterior predictive function calculates the mean and covariance of the GP posterior at new test points, using the kernel and training data. | |
| The noise term sigma_y accounts for observation (aleatoric) noise in training data. | |
| """ | |
| import numpy as np | |
| from numpy.linalg import inv |