A posteriori certification of PDE approximations with particular application to neural networks

Lewin Ernst, Nikolaos Rekatsinas, Karsten Urban

We propose rigorous and efficiently computable lower and upper a posteriori error bounds for given approximations to PDEs on a given domain, which might be geometrically complex. T…