J. Gopalakrishnan

Variationally correct loss functions for nonlinear parametric problems and their neural approximations

We construct computable a posteriori error estimators for parametric families of nonlinear elliptic problems by measuring the residual of a variational formulation in the dual norm of a closed subspace of the test space. A single abstract theorem shows that the resulting estimator is bounded above and below by the erro...