R. Musah

Inverted model selection in physics-informed neural networks: when a lower residual selects a worse solution

Testing across six architectures--MLP, cPINN, XPINN, hp-VPINN, and physics-informed DeepONet and FNO--inverts the ranking in 46 of 48 pairs, indicating that this variability is problem-dependent rather than specific to the approximator.