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Causal Physics-Informed Neural Networks Training System For Physical Simulation
A computer-based training system improves physics-informed neural networks (PINNs) training by weighted residual loss terms to account for physical causality. Problem: Conventional PINNs can struggle with dynamical systems that show multi-scale, chaotic, or turbulent behavior. Existing formulations may fail to respect the spatio-temporal causal structure...
Published: 7/28/2026   |   Updated: 7/28/2026   |   Inventor(s): Paris Perdikaris, Sifan Wang
Keywords(s): Artificial Intelligence (AI) & Machine Learning, Software
Category(s): Technology Classifications > Computer Information Systems, Technology Classifications > Imaging