def METHOD_NAME(
    p: Union[Gaussian, MarkovGaussian],
    mean: mfn.Identity,
    _: None,
    kernel: kernels.Linear,
    inducing_variable: InducingPoints,
    nghp: None = None,
) -> tf.Tensor:
    """
    Compute the expectation:
    expectation[n] = <x_n K_{x_n, Z}>_p(x_n)
        - K_{.,} :: Linear kernel
    or the equivalent for MarkovGaussian
    :return: NxDxM
    """
    return tf.linalg.adjoint(expectation(p, (kernel, inducing_variable), mean))