Konstantin Karchev

Recovering Sharp Conductivity Features in the Finite-Data Calderón Problem with Physics-Informed Neural Networks

Ali AlHadi Kalout, Pablo Tejerina-Pérez, Konstantin Karchev, Pedro Tarancón-Álvarez, Leonid Sarieddine, Raul Jimenez, et al.

Physics-informed neural networks (PINNs) have recently emerged as a promising framework for addressing the Calderón inverse problem from limited boundary data. In this work, we revisit neural Calderón inversion by introducing multiscale boundary excitations based on randomized wa…Read more