Sophie Moufawad

Standard PINN methods struggle with local convergence, but a two-stage training approach can reliably recover parameters even from poor initial guesses.

PINNs offer a computationally competitive alternative to traditional numerical methods for solving both direct and inverse problems involving complex PDEs, even when closed-form solutions are unavailable.