Siavash Khodakarami

Physics-informed Kolmogorov–Arnold networks (PIKANs) for noise-robust reconstruction of boiling heat flux from infrared measurements

Recovering a noise-amplified inverse quantity from corrupted boundary data is a recurring problem in physics-informed learning for real-world applications. Specifically, small perturbations in the measured field are magnified through the spatial derivatives needed to reconstruct...