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Active Operator Inference for Learning Low-Dimensional Dynamical-System Models from Noisy Data

Journal Article · · SIAM Journal on Scientific Computing
DOI:https://doi.org/10.1137/21m1439729· OSTI ID:2421167
 [1];  [2];  [2];  [2]
  1. Courant Institute of Mathematical Sciences, New York University, New York, NY 10012 USA.; OSTI
  2. Courant Institute of Mathematical Sciences, New York University, New York, NY 10012 USA.
Not provided.
Research Organization:
New York Univ. (NYU), NY (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
DOE Contract Number:
SC0019334
OSTI ID:
2421167
Journal Information:
SIAM Journal on Scientific Computing, Journal Name: SIAM Journal on Scientific Computing Journal Issue: 4 Vol. 45; ISSN 1064-8275
Publisher:
Society for Industrial and Applied Mathematics (SIAM)
Country of Publication:
United States
Language:
English

References (52)

A framework for the solution of the generalized realization problem journal September 2007
Sparse dynamics for partial differential equations journal March 2013
An eigensystem realization algorithm for modal parameter identification and model reduction journal September 1985
Dynamic mode decomposition of numerical and experimental data journal July 2010
Reduced basis approximation and a posteriori error estimation for affinely parametrized elliptic coercive partial differential equations journal September 2007
Exact Recovery of Chaotic Systems from Highly Corrupted Data journal January 2017
Reduced order modeling for nonlinear structural analysis using Gaussian process regression journal November 2018
Stability of Discrete Empirical Interpolation and Gappy Proper Orthogonal Decomposition with Randomized and Deterministic Sampling Points journal January 2020
Refined Perturbation Bounds for Eigenvalues of Hermitian and Non-Hermitian Matrices journal January 2009
Investigation of Sampling Strategies for Reduced-Order Models of Rocket Combustors conference January 2021
A New Approach to Modeling Multiport Systems From Frequency-Domain Data journal January 2010
Extracting Sparse High-Dimensional Dynamics from Limited Data journal January 2018
An ‘empirical interpolation’ method: application to efficient reduced-basis discretization of partial differential equations journal November 2004
Learning Physics-Based Reduced-Order Models for a Single-Injector Combustion Process journal June 2020
Inexact solves in interpolatory model reduction journal April 2012
Non-intrusive reduced order modeling of nonlinear problems using neural networks journal June 2018
On the Sample Complexity of the Linear Quadratic Regulator journal August 2019
A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition journal June 2015
Fast System Identification and Model Reduction Solvers journal January 2007
Data-Driven Parametrized Model Reduction in the Loewner Framework journal January 2014
Finite sample properties of system identification methods journal August 2002
Data-Driven Sparse Sensor Placement for Reconstruction: Demonstrating the Benefits of Exploiting Known Patterns journal May 2018
Approximation of Large-Scale Dynamical Systems book January 2005
Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process journal January 2021
On the Scalar Rational Interpolation Problem journal January 1986
The diffusive Lotka-Volterra model as applied to the population dynamics of the German carp and predator and prey species in the Danube River basin journal August 1994
Nonlinear System Identification: A User-Oriented Road Map journal December 2019
A New Selection Operator for the Discrete Empirical Interpolation Method---Improved A Priori Error Bound and Extensions journal January 2016
Vector Fitting for Matrix-valued Rational Approximation journal January 2015
Missing Point Estimation in Models Described by Proper Orthogonal Decomposition journal November 2008
Data-driven operator inference for nonintrusive projection-based model reduction journal July 2016
Rational approximation of frequency domain responses by vector fitting journal July 1999
Operator Inference of Non-Markovian Terms for Learning Reduced Models from Partially Observed State Trajectories journal August 2021
Data-driven discovery of partial differential equations journal April 2017
Data-driven reduced order modeling for time-dependent problems journal March 2019
Spectral analysis of nonlinear flows journal November 2009
Data-driven model order reduction of quadratic-bilinear systems: The Loewner framework for QB systems journal July 2018
Discovering governing equations from data by sparse identification of nonlinear dynamical systems journal March 2016
Nonlinear Model Reduction via Discrete Empirical Interpolation journal January 2010
Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems journal May 2020
SubTSBR to tackle high noise and outliers for data-driven discovery of differential equations journal March 2021
Probabilistic error estimation for non-intrusive reduced models learned from data of systems governed by linear parabolic partial differential equations journal May 2021
From Fixed-X to Random-X Regression: Bias-Variance Decompositions, Covariance Penalties, and Prediction Error Estimation journal February 2019
A learning theory approach to system identification and stochastic adaptive control journal March 2008
Effectively Subsampled Quadratures for Least Squares Polynomial Approximations journal January 2017
Tangential interpolation-based eigensystem realization algorithm for MIMO systems journal June 2016
Deep learning of dynamics and signal-noise decomposition with time-stepping constraints journal November 2019
A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems journal January 2015
On dynamic mode decomposition: Theory and applications journal December 2014
Model Reduction of Bilinear Systems in the Loewner Framework journal January 2016
Sampling Low-Dimensional Markovian Dynamics for Preasymptotically Recovering Reduced Models from Data with Operator Inference journal January 2020
Kernel Analog Forecasting: Multiscale Test Problems journal January 2021

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