# Covariance Functions#

 Constant valued covariance function. `WhiteNoise`(sigma) White noise covariance function. `ExpQuad`(input_dim[, ls, ls_inv, active_dims]) The Exponentiated Quadratic kernel. `RatQuad`(input_dim, alpha[, ls, ls_inv, ...]) The Rational Quadratic kernel. `Exponential`(input_dim[, ls, ls_inv, active_dims]) The Exponential kernel. `Matern52`(input_dim[, ls, ls_inv, active_dims]) The Matern kernel with nu = 5/2. `Matern32`(input_dim[, ls, ls_inv, active_dims]) The Matern kernel with nu = 3/2. `Linear`(input_dim, c[, active_dims]) The Linear kernel. `Polynomial`(input_dim, c, d, offset[, ...]) The Polynomial kernel. `Cosine`(input_dim[, ls, ls_inv, active_dims]) The Cosine kernel. `Periodic`(input_dim, period[, ls, ls_inv, ...]) The Periodic kernel. `WarpedInput`(input_dim, cov_func, warp_func) Warp the inputs of any kernel using an arbitrary function defined using PyTensor. `Gibbs`(input_dim, lengthscale_func[, args, ...]) The Gibbs kernel. `Coregion`(input_dim[, W, kappa, B, active_dims]) Covariance function for intrinsic/linear coregionalization models. `ScaledCov`(input_dim, cov_func, scaling_func) Construct a kernel by multiplying a base kernel with a scaling function defined using PyTensor. `Kron`(factor_list) Form a covariance object that is the kronecker product of other covariances.