  The development of efficient numerical methods for kinetic equations with
stochastic parameters is a challenge due to the high dimensionality of the
problem. Recently we introduced a multiscale control variate strategy which is
capable to accelerate considerably the slow convergence of standard Monte Carlo
methods for uncertainty quantification. Here we generalize this class of
methods to the case of multiple control variates. We show that the additional
degrees of freedom can be used to improve further the variance reduction
properties of multiscale control variate methods.
