Learning to Forecast Dynamical Systems from Streaming Data-Reference-Cited by-同舟云学术

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Learning to Forecast Dynamical Systems from Streaming Data

Published:2023-05-05 Issue:2 Volume:22 Page:527-558
ISSN:1536-0040
Container-title:SIAM Journal on Applied Dynamical Systems
language:en
Short-container-title:SIAM J. Appl. Dyn. Syst.

Author:

Giannakis Dimitrios¹^ORCID,Henriksen Amelia²,Tropp Joel A.³^ORCID,Ward Rachel⁴^ORCID

Affiliation:

1. Department of Mathematics, Dartmouth College, Hanover, NH 03766 USA.

2. Sandia National Laboratories, Albuquerque, NM 87185 USA, and Oden Institute, University of Texas at Austin, Austin, TX 78712-1229 USA.

3. Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA 91125 USA.

4. Department of Mathematics, University of Texas at Austin, Austin, TX 78712 USA .

Funder

National Science Foundation

Office of Naval Research

Air Force Office of Scientific Research

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Modeling and Simulation,Analysis

Reference72 articles.

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

2. Kernel Analog Forecasting of Tropical Intraseasonal Oscillations

3. Generative Stochastic Modeling of Strongly Nonlinear Flows with Non-Gaussian Statistics

4. Theory of reproducing kernels

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