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Koopman operator based models emerged as the leading methodology for machine learning of dynamical systems. But their scope is much larger. In fact they present a new take on modeling of physical systems, and even language. In this article I present some of the underlying mathematical structures, applications, connections to other methodologies such as transformer architectures

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