Machine Learning, Dynamical Systems and Control

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Mitsubishi Electric Research Laboratories (MERL)

UW and MERL scientists collaborate on reduced-order modeling of physical systems for forecasting, control, and sensing applications. In particular, a framework for incorporating knowledge of physics into neural-network-based reduced-order models was developed by Aleksei Sholokhov (UW) and Yuying Liu (UW) under the guidance of Hassan Mansour (MERL), Joshua Rapp (MERL), and Saleh Nabi (MERL). They showed that resulting models predict more accurately, extrapolate better in unforeseen scenarios, and less sensitive to noise. This work already resulted in several papers and remains an active research direction.