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machine learning is emerging as a promising avenue for solving problems in physics and engineering. Particularly, physics-informed neural networks (PINNs) have shown remarkable potential to solve problems
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solid foundation for trustworthy machine learning tools and physics-informed neural networks for power system applications. The Division for Power and Energy Systems of DTU Wind and Energy Systems
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