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RISGradient-Driven Physics Informed Neural Networks for Conduction Heat Transfer and Incompressible Laminar Flow
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Abstract. Physics-Informed Neural Networks (PINNs) have opened new possibilities for solving partial differential equations (PDEs) by embedding physical laws directly into the learning process. However, despite their ...