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In this article, we develop a new methodology, Hybrid-Sparse Identification of Nonlinear Dynamics (Hybrid-SINDy), which identifies separate nonlinear dynamical regimes, employs information theory t
In this paper, we provide deterministic non-asymptotic error bounds for fitting a linear model to the observed time-series data, with a particular attention to the role of symmetry and eigenvalue m
We develop a new generalization of Koopman operator theory that incorporates the effects of inputs and control.
The main focus of this work is on the use of PSPO to maximize the pseudo-likelihood of a stochastic epidemiological model to data from a 1861 measles outbreak in Hagelloch, Germany.
We present a universal, data-driven decomposition of chaos as an intermittently forced linear system.
Containing the recent West African outbreak of Ebola virus (EBOV) required the deployment of substantial global resources.