Learning dynamical systems from data: a simple cross-validation perspective. IV: Case with partial observations (Q6096532)

scientific article; zbMATH DE number 7736383

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English	Learning dynamical systems from data: a simple cross-validation perspective. IV: Case with partial observations	scientific article; zbMATH DE number 7736383

Statements

instance of

scholarly article

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title

Learning dynamical systems from data: a simple cross-validation perspective. IV: Case with partial observations (English)

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author

Boumediene Hamzi

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Houman Owhadi

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Ioannis G. Kevrekidis

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published in

Physica D

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publication date

12 September 2023

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zbMATH Keywords

learning dynamical systems

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kernel flows

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partial observations

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computational graph completion

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MaRDI profile type

MaRDI publication profile

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full work available at URL

https://doi.org/10.1016/j.physd.2023.133853

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cites work

Q4346204

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Nonlinear prediction of chaotic time series

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Discovering governing equations from data by sparse identification of nonlinear dynamical systems

0 references

Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data

0 references

Solving and learning nonlinear PDEs with Gaussian processes

0 references

Computational graph completion

0 references

Kernel methods for center manifold approximation and a weak data-based version of the center manifold theorem

0 references

Dimensionality reduction of complex metastable systems via kernel embeddings of transition manifolds

0 references

Data-driven approximation of the Koopman generator: model reduction, system identification, and control

0 references

Operator-theoretic framework for forecasting nonlinear time series with kernel analog techniques

0 references

Kernel Methods for the Approximation of Nonlinear Systems

0 references

Kernel methods for the approximation of some key quantities of nonlinear systems

0 references

A note on kernel methods for multiscale systems with critical transitions

0 references

Learning ``best'' kernels from data in Gaussian process regression. With application to aerodynamics

0 references

A note on microlocal kernel design for some slow-fast stochastic differential equations with critical transitions and application to EEG signals

0 references

Learning dynamical systems from data: a simple cross-validation perspective. I: Parametric kernel flows

0 references

9 Kernel methods for surrogate modeling

0 references

Do ideas have shape? Idea registration as the continuous limit of artificial neural networks

0 references

Kernel flows: from learning kernels from data into the abyss

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Learning dynamical systems from data: a simple cross-validation perspective. III: Irregularly-sampled time series

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One-shot learning of stochastic differential equations with data adapted kernels

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Machine learning for prediction with missing dynamics

0 references

Operator-Adapted Wavelets, Fast Solvers, and Numerical Homogenization

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On the mathematical foundations of learning

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Theory of Reproducing Kernels

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Local error estimates for radial basis function interpolation of scattered data

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Bayesian Numerical Homogenization

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Identifiers

DOI

10.1016/j.physd.2023.133853

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Mathematics Subject Classification ID

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Sitelinks

Mathematics(1 entry)

mardi Publication:6096532