most citedQCPINN: Quantum-Classical Physics-Informed Neural Networks for Solving PDEs

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cs.LG2025★ 1 cited

Learning Fluid-Structure Interaction with Physics-Informed Machine Learning and Immersed Boundary Methods

Afrah Farea, Saiful Khan, Reza Daryani +2

Physics-informed neural networks (PINNs) have emerged as a promising approach for solving complex fluid dynamics problems, yet their application to fluid-structure interaction (FSI…