Gnankan Landry Regis N'guessan

Discovering Scaling Exponents with Physics-Informed Müntz-Szász Networks

Physical systems near singularities, interfaces, and critical points exhibit power-law scaling, yet standard neural networks leave the governing exponents implicit. We introduce physics-informed M\"untz-Sz\'asz Networks (MSN-PINN), a power-law basis network that treats scaling exponents as trainable…