Pages that link to "Item:Q5348477"
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The following pages link to Kernel Methods for the Approximation of Nonlinear Systems (Q5348477):
Displaying 32 items.
- Kernel methods for the approximation of some key quantities of nonlinear systems (Q1654461) (← links)
- Dimensionality reduction of complex metastable systems via kernel embeddings of transition manifolds (Q2022651) (← links)
- Kernel methods for center manifold approximation and a weak data-based version of the center manifold theorem (Q2077601) (← links)
- Learning dynamical systems from data: a simple cross-validation perspective. I: Parametric kernel flows (Q2077645) (← links)
- One-shot learning of stochastic differential equations with data adapted kernels (Q2111726) (← links)
- Lift \& learn: physics-informed machine learning for large-scale nonlinear dynamical systems (Q2115511) (← links)
- A long short-term memory embedding for hybrid uplifted reduced order models (Q2125587) (← links)
- Approximation of Lyapunov functions from noisy data (Q2192453) (← links)
- Kernel embedding based variational approach for low-dimensional approximation of dynamical systems (Q2237840) (← links)
- \texttt{emgr} -- the empirical Gramian framework (Q2287472) (← links)
- Kernel method and linear recurrence system (Q2483349) (← links)
- Kernel method and system of functional equations (Q2519703) (← links)
- Learning dynamical systems from data: a simple cross-validation perspective. III: Irregularly-sampled time series (Q2677775) (← links)
- A note on microlocal kernel design for some slow-fast stochastic differential equations with critical transitions and application to EEG signals (Q2700697) (← links)
- Kernel-based methods for parameter estimation in multidimensional systems (Q2851166) (← links)
- (Q2970771) (← links)
- 9 Kernel methods for surrogate modeling (Q3384280) (← links)
- (Q3776933) (← links)
- (Q4391319) (← links)
- New characterizations of reproducing kernel Hilbert spaces and applications to metric geometry (Q5004074) (← links)
- Balanced Truncation Model Reduction for Lifted Nonlinear Systems (Q5049229) (← links)
- Block Basis Factorization for Scalable Kernel Evaluation (Q5203970) (← links)
- Kernel Methods for the Approximation of Nonlinear Systems (Q5348477) (← links)
- (Q5468299) (← links)
- Kernel-Based Models for System Analysis (Q6047030) (← links)
- Model Reduction for Nonlinear Systems by Balanced Truncation of State and Gradient Covariance (Q6054284) (← links)
- Learning dynamical systems from data: a simple cross-validation perspective. IV: Case with partial observations (Q6096532) (← links)
- Learning dynamical systems from data: a simple cross-validation perspective. V: Sparse kernel flows for 132 chaotic dynamical systems (Q6496480) (← links)
- Simplicity bias, algorithmic probability, and the random logistic map (Q6554925) (← links)
- Learn to synchronize, synchronize to learn (Q6556925) (← links)
- Bridging algorithmic information theory and machine learning: a new approach to kernel learning (Q6558847) (← links)
- Hausdorff metric based training of kernels to learn attractors with application to 133 chaotic dynamical systems (Q6558876) (← links)
