Pages that link to "Item:Q317185"
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The following pages link to A kernel-based method for data-driven Koopman spectral analysis (Q317185):
Displaying 50 items.
- On the numerical approximation of the Perron-Frobenius and Koopman operator (Q333775) (← links)
- Towards tensor-based methods for the numerical approximation of the Perron-Frobenius and Koopman operator (Q523959) (← links)
- Data-driven model reduction and transfer operator approximation (Q722011) (← links)
- Total-variation mode decomposition (Q826134) (← links)
- A data-driven approximation of the koopman operator: extending dynamic mode decomposition (Q897161) (← links)
- High-dimensional time series prediction using kernel-based koopman mode regression (Q1696900) (← links)
- Applied Koopman theory for partial differential equations and data-driven modeling of spatio-temporal systems (Q1723113) (← links)
- Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control (Q1796994) (← links)
- Koopman operator framework for time series modeling and analysis (Q2022703) (← links)
- Geometric considerations of a good dictionary for Koopman analysis of dynamical systems: cardinality, ``primary eigenfunction,'' and efficient representation (Q2025462) (← links)
- Dynamic mode decomposition for continuous time systems with the Liouville operator (Q2062874) (← links)
- Low-rank dynamic mode decomposition: an exact and tractable solution (Q2062877) (← links)
- Liouville operators over the Hardy space (Q2069910) (← links)
- Tensor-based computation of metastable and coherent sets (Q2077619) (← links)
- Data-driven operator theoretic methods for phase space learning and analysis (Q2083237) (← links)
- Data-driven reduced-order modeling for nonautonomous dynamical systems in multiscale media (Q2112501) (← links)
- Lift \& learn: physics-informed machine learning for large-scale nonlinear dynamical systems (Q2115511) (← links)
- Data-driven approximation of the Koopman generator: model reduction, system identification, and control (Q2115518) (← links)
- Mesoscale informed parameter estimation through machine learning: a case-study in fracture modeling (Q2125026) (← links)
- Ensemble-based method for the inverse Frobenius-Perron operator problem: data-driven global analysis from spatiotemporal ``movie'' data (Q2127388) (← links)
- Deep learning nonlinear multiscale dynamic problems using Koopman operator (Q2133546) (← links)
- Data-driven eigensolution analysis based on a spatio-temporal Koopman decomposition, with applications to high-order methods (Q2136484) (← links)
- Correcting noisy dynamic mode decomposition with Kalman filters (Q2137999) (← links)
- tgEDMD: approximation of the Kolmogorov operator in tensor train format (Q2146443) (← links)
- Assessment of end-to-end and sequential data-driven learning for non-intrusive modeling of fluid flows (Q2190672) (← links)
- Evaluating the accuracy of the dynamic mode decomposition (Q2192452) (← links)
- Time-resolved denoising using model order reduction, dynamic mode decomposition, and Kalman filter and smoother (Q2194437) (← links)
- A data-driven non-linear assimilation framework with neural networks (Q2225345) (← links)
- Kernel embedding based variational approach for low-dimensional approximation of dynamical systems (Q2237840) (← links)
- Data-driven spectral analysis of the Koopman operator (Q2300750) (← links)
- Variational approach for learning Markov processes from time series data (Q2303757) (← links)
- Eigendecompositions of transfer operators in reproducing kernel Hilbert spaces (Q2303767) (← links)
- Spatiotemporal pattern extraction by spectral analysis of vector-valued observables (Q2327837) (← links)
- Nonlinear observability via Koopman analysis: characterizing the role of symmetry (Q2663863) (← links)
- Operator inference and physics-informed learning of low-dimensional models for incompressible flows (Q2672189) (← links)
- Extension of dynamic mode decomposition for dynamic systems with incomplete information based on t-model of optimal prediction (Q2681120) (← links)
- Extended dynamic mode decomposition for two paradigms of non-linear dynamical systems (Q2684647) (← links)
- Learning dynamical systems using local stability priors (Q2696118) (← links)
- Multiresolution dynamic mode decomposition (Q2808171) (← links)
- Dynamic mode decomposition for financial trading strategies (Q4554232) (← links)
- Koopman Operator Family Spectrum for Nonautonomous Systems (Q4562415) (← links)
- Koopman analysis of the long-term evolution in a turbulent convection cell (Q4582914) (← links)
- Optimized Sampling for Multiscale Dynamics (Q4627447) (← links)
- On Matching, and Even Rectifying, Dynamical Systems through Koopman Operator Eigenfunctions (Q4686615) (← links)
- Sparsity-promoting algorithms for the discovery of informative Koopman-invariant subspaces (Q4987934) (← links)
- Estimation of the Koopman Generator by Newton's Extrapolation (Q4992258) (← links)
- Linearly Constrained Linear Quadratic Regulator from the Viewpoint of Kernel Methods (Q5009773) (← links)
- Deep learning models for global coordinate transformations that linearise PDEs (Q5014841) (← links)
- Numerical methods to evaluate Koopman matrix from system equations* (Q5048531) (← links)
- Koopman analysis of quantum systems* (Q5057844) (← links)
