def METHOD_NAME(
    inducing_variable: SharedIndependentInducingVariables,
    kernel: SeparateIndependent,
    Xnew: TensorType,
) -> tf.Tensor:
    return tf.stack(
        [Kuf(inducing_variable.inducing_variable, k, Xnew) for k in kernel.kernels], axis=0
    )