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While physics-informed neural networks (PINNs) have been proven effective for low-dimensional partial differential equations (PDEs), the computational cost remains a hurdle in high-dimensional scenarios.
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Zheyuan Hu, Ameya D. Jagtap, George Em Karniadakis, and Kenji Kawaguchi · 2022
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