Pages that link to "Item:Q4686615"
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The following pages link to On Matching, and Even Rectifying, Dynamical Systems through Koopman Operator Eigenfunctions (Q4686615):
Displaying 17 items.
- Comparison of systems with complex behavior (Q1888050) (← links)
- Geometric considerations of a good dictionary for Koopman analysis of dynamical systems: cardinality, ``primary eigenfunction,'' and efficient representation (Q2025462) (← links)
- Data-driven operator theoretic methods for phase space learning and analysis (Q2083237) (← links)
- Nonlinear observability via Koopman analysis: characterizing the role of symmetry (Q2663863) (← links)
- Manifold learning for organizing unstructured sets of process observations (Q3303828) (← links)
- On explaining the surprising success of reservoir computing forecaster of chaos? The universal machine learning dynamical system with contrast to VAR and DMD (Q4983648) (← links)
- Koopman Operator, Geometry, and Learning of Dynamical Systems (Q5029862) (← links)
- Modern Koopman Theory for Dynamical Systems (Q5075835) (← links)
- On the Koopman Operator of Algorithms (Q5109369) (← links)
- Spectral analysis of the Koopman operator for partial differential equations (Q5140900) (← links)
- Koopman Operators and the $3x+1$-Dynamical System (Q5164902) (← links)
- Discrete-time nonlinear feedback linearization via physics-informed machine learning (Q6078485) (← links)
- Koopman spectral analysis of elementary cellular automata (Q6557723) (← links)
- Deep learning enhanced dynamic mode decomposition (Q6560590) (← links)
- Slow invariant manifolds of singularly perturbed systems via physics-informed machine learning (Q6573172) (← links)
- Data-driven linearization of dynamical systems (Q6617274) (← links)
- Slow invariant manifolds of fast-slow systems of ODEs with physics-informed neural networks (Q6661630) (← links)
