We study H(div) preconditioning for the saddle-point systems that arise in a stochastic Galerkin mixed formulation of the steady-state diffusion problem with random data. The key i...
Howard C. Elman, Darran G. Furnival, Catherine E. ...
Generalizing the approach of a previous work [15] the authors present multilevel preconditioners for three-dimensional (3D) elliptic problems discretized by a family of Rannacher ...
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
The characteristic methods are known to be very efficient for convection-diffusion problems including the Navier-Stokes equations. Convergence is established when the integrals ar...
Semidiscrete finite element approximation of the linear stochastic wave equation with additive noise is studied in a semigroup framework. Optimal error estimates for the determinis...