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DOE OSTI · 1808822

Learning Implicit Models of Complex Dynamical Systems From Partial Observations [Slides]

Rupe, Adam Thomas
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Abstract

Conclusions: certain data-driven models do implicitly what physics simulations do explicitly; theoretical underpinnings in Koopman theory, delay-coordinate embeddings, and Mori-Zwanzig formalism; best approach for given system with finite data an open question; physics-informed machine learning (PIML) emerging framework for combining explicit and implicit modeling.

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BibTeXRIS

Rupe, Adam Thomas. 2021-07-19. Learning Implicit Models of Complex Dynamical Systems From Partial Observations [Slides]. https://doi.org/10.2172/1808822

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