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Discovering sparse interpretable dynamics from partial observations

Physics

Discovering sparse interpretable dynamics from partial observations

P. Y. Lu, J. A. Bernad, et al.

Understanding the governing equations of nonlinear dynamical systems is paramount, especially for those that are partially observed. This innovative research by Peter Y. Lu, Joan Ariño Bernad, and Marin Soljačić introduces a machine learning framework that seamlessly reconstructs system states and discovers governing equations, elevating the potential for accurate modeling in complex physical systems.... show more
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28
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47
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