Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition | Paper Citation Record

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This paper cites Efﬁcient identiﬁcation of linear evolutions in nonlinear vector ﬁelds: Koopman invariant subspaces,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Efﬁcient identiﬁcation of linear evolutions in nonlinear vector ﬁelds: Koopman invariant subspaces,

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This paper cites Hamiltonian systems and transformation in Hilbert space,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Hamiltonian systems and transformation in Hilbert space,

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This paper cites Dynamical systems of continuous spectra,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Dynamical systems of continuous spectra,

Reference 3

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This paper cites Spectral properties of dynamical systems, model reduction and decompositions,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Spectral properties of dynamical systems, model reduction and decompositions,

Reference 4

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This paper cites Spectral analysis of nonlinear ﬂows,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Spectral analysis of nonlinear ﬂows,

Reference 5

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This paper cites Applied Koopmanism,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Applied Koopmanism,

Reference 6

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This paper cites Koopman operator framework for constrained state estimation,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Koopman operator framework for constrained state estimation,

Reference 7

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This paper cites A robust data-driven Koopman Kalman ﬁlter for power systems dynamic state estimation,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition A robust data-driven Koopman Kalman ﬁlter for power systems dynamic state estimation,

Reference 8

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This paper cites Koopman-based lifting techniques for nonlinear systems identiﬁcation,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Koopman-based lifting techniques for nonlinear systems identiﬁcation,

Reference 9

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This paper cites Nonlinear system identiﬁ- cation of soft robot dynamics using Koopman operator theory,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Nonlinear system identiﬁ- cation of soft robot dynamics using Koopman operator theory,

Reference 10

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This paper cites Sparse sensing and DMD-based identiﬁcation of ﬂow regimes and bifurcations in complex ﬂows,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Sparse sensing and DMD-based identiﬁcation of ﬂow regimes and bifurcations in complex ﬂows,

Reference 11

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This paper cites Operator theoretic framework for optimal placement of sensors and actuators for control of nonequilibrium dynamics,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Operator theoretic framework for optimal placement of sensors and actuators for control of nonequilibrium dynamics,

Reference 12

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This paper cites Data-driven model reduction and transfer operator approximation,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Data-driven model reduction and transfer operator approximation,

Reference 13

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This paper cites Nonlinear model order reduction via dynamic mode decomposition,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Nonlinear model order reduction via dynamic mode decomposition,

Reference 14

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This paper cites Linear predictors for nonlinear dynamical sys- tems: Koopman operator meets model predictive control,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Linear predictors for nonlinear dynamical sys- tems: Koopman operator meets model predictive control,

Reference 15

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This paper cites A data-driven Koopman model predictive control framework for nonlinear flows.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition A data-driven Koopman model predictive control framework for nonlinear flows

Reference 16

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This paper cites Koopman operator-based model reduction for switched-system control of PDEs,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Koopman operator-based model reduction for switched-system control of PDEs,

Reference 17

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This paper cites Feedback stabilization using Koop- man operator,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Feedback stabilization using Koop- man operator,

Reference 18

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This paper cites Data-driven discovery of Koopman eigenfunctions for control.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Data-driven discovery of Koopman eigenfunctions for control

Reference 19

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This paper cites Pulse-based control using Koopman operator under parametric uncertainty,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Pulse-based control using Koopman operator under parametric uncertainty,

Reference 20

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This paper cites Data-driven feedback stabilization of nonlinear systems: Koopman-based model predictive control.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Data-driven feedback stabilization of nonlinear systems: Koopman-based model predictive control

Reference 21

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This paper cites Local Koopman operators for data-driven control of robotic systems,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Local Koopman operators for data-driven control of robotic systems,

Reference 22

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This paper cites Control-oriented modeling of soft robotic swimmer with Koop- man operators,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Control-oriented modeling of soft robotic swimmer with Koop- man operators,

Reference 23

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This paper cites Global stability analysis using the eigen- functions of the Koopman operator,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Global stability analysis using the eigen- functions of the Koopman operator,

Reference 24

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This paper cites Dynamic mode decomposition of numerical and experi- mental data,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Dynamic mode decomposition of numerical and experi- mental data,

Reference 25

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This paper cites Variants of dynamic mode decomposition: boundary condition, Koopman, and Fourier analyses,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Variants of dynamic mode decomposition: boundary condition, Koopman, and Fourier analyses,

Reference 26

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This paper cites On dynamic mode decomposition: theory and applications,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition On dynamic mode decomposition: theory and applications,

Reference 27

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This paper cites Dynamic mode decomposition for large and streaming datasets,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Dynamic mode decomposition for large and streaming datasets,

Reference 28

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Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Online dynamic mode decomposition for time-varying systems,

Reference 29

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This paper cites A parallel and streaming dynamic mode decomposition algorithm with ﬁnite precision error analysis for large data,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition A parallel and streaming dynamic mode decomposition algorithm with ﬁnite precision error analysis for large data,

Reference 30

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Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Characterizing and correcting for the effect of sensor noise in the dynamic mode decomposition,

Reference 31

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This paper cites De-biasing the dynamic mode decomposition for applied Koopman spectral analysis of noisy datasets,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition De-biasing the dynamic mode decomposition for applied Koopman spectral analysis of noisy datasets,

Reference 32

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Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Sparsity-promoting dynamic mode decomposition,

Reference 33

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Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Higher-order dynamic mode decom- position,

Reference 34

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Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition A data-driven approximation of the Koopman operator: Extending dynamic mode decomposition,

Reference 35

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This paper cites On convergence of extended dynamic mode decomposition to the Koopman operator,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition On convergence of extended dynamic mode decomposition to the Koopman operator,

Reference 36

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Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Approximating the Koopman operator using noisy data: noise-resilient extended dynamic mode decomposition,

Reference 37

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This paper cites Lift & learn: Physics-informed machine learning for large-scale nonlinear dynamical systems,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Lift & learn: Physics-informed machine learning for large-scale nonlinear dynamical systems,

Reference 38

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This paper cites Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator,

Reference 39

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This paper cites Learning Koopman invariant subspaces for dynamic mode decomposition,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Learning Koopman invariant subspaces for dynamic mode decomposition,

Reference 40

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This paper cites Learning deep neural network representations for Koopman operators of nonlinear dynamical systems,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Learning deep neural network representations for Koopman operators of nonlinear dynamical systems,

Reference 41

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This paper cites Linearly recurrent autoencoder networks for learning dynamics,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Linearly recurrent autoencoder networks for learning dynamics,

Reference 42

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This paper cites Koop- man invariant subspaces and ﬁnite linear representations of nonlinear dynamical systems for control,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Koop- man invariant subspaces and ﬁnite linear representations of nonlinear dynamical systems for control,

Reference 43

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This paper cites Optimal construction of Koopman eigen- functions for prediction and control,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Optimal construction of Koopman eigen- functions for prediction and control,

Reference 44

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Observation cb581edd-8f9c-476a-bef3-4b5da960fb94 · outbound

This paper cites Data-driven approximation of the Koopman generator: Model reduction, system identification, and control.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Data-driven approximation of the Koopman generator: Model reduction, system identification, and control

Reference 45

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Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Unresolved cited work

Reference 46

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This paper cites Optimal construction of Koopman eigenfunctions for prediction and control,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Optimal construction of Koopman eigenfunctions for prediction and control,

Reference 47

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This paper cites Tutorial: Complexity analysis of Singular Value Decomposition and its variants.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Tutorial: Complexity analysis of Singular Value Decomposition and its variants

Reference 48

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This paper cites Symmetric gauge functions and unitarily invariant norms,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Symmetric gauge functions and unitarily invariant norms,

Reference 49

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This paper cites Overview of total least-squares meth- ods,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Overview of total least-squares meth- ods,

Reference 50

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This paper cites The approximation of one matrix by another of lower rank,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition The approximation of one matrix by another of lower rank,

Reference 51

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Observation bdfe2892-0b9e-4518-aebd-347108c82432 · outbound

This paper cites Non-local linearization of nonlinear differential equations via polyﬂows,.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition Non-local linearization of nonlinear differential equations via polyﬂows,

Reference 52

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Observation 8144b77d-f1c0-41af-8d1f-da05d5f64fc6 · outbound

This paper cites degree, in 2013, and M.Sc.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition degree, in 2013, and M.Sc

Reference 1991

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Observation 4227d4f5-9a84-498f-a0bd-fba4f560a922 · outbound

This paper cites He was an Assistant Professor with the Department of Applied Mathematics and Statistics, University of California, Santa Cruz, CA, USA, from 2004 to 2007.

Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition He was an Assistant Professor with the Department of Applied Mathematics and Statistics, University of California, Santa Cruz, CA, USA, from 2004 to 2007

Reference 2001

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