most citedUsing Noisy or Incomplete Data to Discover Models of Spatiotemporal Dynamics

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physics.flu-dyn2021

Robust learning from noisy, incomplete, high-dimensional experimental data via physically constrained symbolic regression

Patrick A. K. Reinbold, Logan M. Kageorge, Michael F. Schatz +1

Machine learning offers an intriguing alternative to first-principles analysis for discovering new physics from experimental data. However, to date, purely data-driven methods have…