Regression-Based Projection for Learning Mori–Zwanzig Operators-Reference-Cited by-同舟云学术

Regression-Based Projection for Learning Mori–Zwanzig Operators

Published:2023-10-13 Issue:4 Volume:22 Page:2890-2926
ISSN:1536-0040
Container-title:SIAM Journal on Applied Dynamical Systems
language:en
Short-container-title:SIAM J. Appl. Dyn. Syst.

Author:

Lin Yen Ting¹^ORCID,Tian Yifeng¹^ORCID,Perez Danny²^ORCID,Livescu Daniel³^ORCID

Affiliation:

1. Information Sciences Group, Computer, Computational and Statistical Sciences Division CCS-3, Los Alamos National Laboratory, Los Alamos, NM 87545 USA. These authors contributed equally.

2. Physics and Chemistry of Materials Group, Theoretical Division T-1, Los Alamos National Laboratory, Los Alamos, NM 87545 USA.

3. Computational Physics and Methods Group, Computer, Computational and Statistical Sciences Division CCS-2, Los Alamos National Laboratory, Los Alamos, NM 87545 USA.

Funder

Los Alamos National Laboratory

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Modeling and Simulation,Analysis

Reference54 articles.

1. Regression and Projection

2. Ergodic Theory, Dynamic Mode Decomposition, and Computation of Spectral Properties of the Koopman Operator

3. On explaining the surprising success of reservoir computing forecaster of chaos? The universal machine learning dynamical system with contrast to VAR and DMD

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

5. Optimal prediction with memory

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