3 problems

The DNNI-based method uses deep neural networks to approximate integrations within a Galerkin method, while traditional quadrature-based Galerkin methods perform these integrations…

Let $K_{n,p}^{{\mathbb{Q}}_\mu}$ be the stiffness matrix considered above, and let $\lambda_j(K_{n,p}^{{\mathbb{Q}}_\mu})$ denote its $j$-th smallest eigenvalue. Asymptotic eigenva…

The ADER-WENO Galerkin predictor is obtained from a nonlinear system involving matrices associated with the temporal and spatial basis functions. For the continuous Galerkin case,…