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Component-Level Evaluation of Adaptive PINN Training for CFD-Oriented Crystal Growth Simulation
Physics-informed neural network (PINN) training minimizes a weighted combination of partial differential equation (PDE), boundary-condition, and initial-condition losses. Because adaptive methods modify these weights during training, their weighted total losses are not always directly comparable. We
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