Covariance Functions#


Constant valued covariance function.


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.


Form a covariance object that is the kronecker product of other covariances.