  We study the regular conditional law of mixed Gaussian Volterra processes
under the influence of model disturbances. More precisely, we study prediction
of Gaussian Volterra processes driven by a Brownian motion in a case where the
Brownian motion is not observable, but only a noisy version is observed. As an
application, we discuss how our result can be applied to variance reduction in
the presence of measurement errors.
