AI RESEARCH
Learning Hidden Physics and System Parameters with Deep Operator Networks
arXiv CS.LG
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ArXi:2412.05133v3 Announce Type: replace Discovering hidden physical laws and identifying governing system parameters from sparse observations are central challenges in computational science and engineering. Existing data-driven methods, such as physics-informed neural networks (PINNs) and sparse regression, are limited by their need for extensive re