Numerical tests indicate that a stochastic Galerkin discretization with embedded slabwise space-time finite elements and GMRES-GMG solvers outperforms Monte-Carlo sampling for random parabolic problems in convergence and algebraic solver statistics.
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Stochastic Galerkin and Monte-Carlo methods for parabolic problems: Numerical performance of variational matrix-free approximations
Numerical tests indicate that a stochastic Galerkin discretization with embedded slabwise space-time finite elements and GMRES-GMG solvers outperforms Monte-Carlo sampling for random parabolic problems in convergence and algebraic solver statistics.