ine">\(f\colon \mathbb{R}^D \mapsto \mathbb{R}\)</span>
as a function of the squared Euclidian distance between <span class="math inline">\(x_i \in \mathbb{R}^D\)</span> and <span class="math inline">\(x_j \in \mathbb{R}^D\)</span>: <span class="math display">\[   \text{cov}(f(x_i),
f(x_j)) = k(x_i, x_j) = \alpha^2 \exp \left(         -
\dfrac{1}{2\rho^2} \sum_{d=1}^D (x_{i,d} - x_{j,d})^2 \right) \]</span> with
<span class="math inline">\(\alpha\)</span> and <span class="math inline">\(\rho\)</span> constr