Nonlinear compressive reduced basis approximation for multi-parameter
elliptic problem
Nonlinear compressive reduced basis approximation for multi-parameter
elliptic problem
Reduced basis methods for approximating the solutions of parameter-dependant partial differential equations (PDEs) are based on learning the structure of the set of solutions - seen as a manifold ${\mathcal S}$ in some functional space - when the parameters vary. This involves investigating the manifold and, in particular, understanding whether …