Pawan Goyal

Adv. Comput. Math., August, 2024

Dominant subspaces of high-fidelity polynomial structured parametric dynamical systems and model reduction.

[BibT_eX]

[DOI]

Adv. Comput. Math., June, 2024

Rank-Minimizing and Structured Model Inference.

[BibT_eX]

[DOI]

Benjamin Peherstorfer

SIAM J. Sci. Comput., 2024

Parameterized Interpolation of Passive Systems.

[BibT_eX]

[DOI]

Paul Van Dooren

SIAM J. Matrix Anal. Appl., 2024

Structure-preserving learning for multi-symplectic PDEs.

[BibT_eX]

[DOI]

Süleyman Yildiz

CoRR, 2024

Active Sampling of Interpolation Points to Identify Dominant Subspaces for Model Reduction.

[BibT_eX]

[DOI]

CoRR, 2024

Divergence-free neural operators for stress field modeling in polycrystalline materials.

[BibT_eX]

[DOI]

Mohammad Khorrami

Jaber Rezaei Mianroodi

Bob Svendsen

Dierk Raabe

CoRR, 2024

Stability-Certified Learning of Control Systems with Quadratic Nonlinearities.

[BibT_eX]

[DOI]

CoRR, 2024

Learning reduced-order Quadratic-Linear models in Process Engineering using Operator Inference.

[BibT_eX]

[DOI]

CoRR, 2024

2023

A Robust SINDy Approach by Combining Neural Networks and an Integral Form.

[BibT_eX]

[DOI]

Ali Forootani

CoRR, 2023

Deep Learning for Structure-Preserving Universal Stable Koopman-Inspired Embeddings for Nonlinear Canonical Hamiltonian Dynamics.

[BibT_eX]

[DOI]

Süleyman Yildiz

CoRR, 2023

Guaranteed Stable Quadratic Models and their applications in SINDy and Operator Inference.

[BibT_eX]

[DOI]

CoRR, 2023

Linearly Implicit Global Energy Preserving Reduced-order Models for Cubic Hamiltonian Systems.

[BibT_eX]

[DOI]

Süleyman Yildiz

CoRR, 2023

Data-Driven Identification of Quadratic Symplectic Representations of Nonlinear Hamiltonian Systems.

[BibT_eX]

[DOI]

CoRR, 2023

Inference of Continuous Linear Systems from Data with Guaranteed Stability.

[BibT_eX]

[DOI]

CoRR, 2023

Dominant Subspaces of High-Fidelity Nonlinear Structured Parametric Dynamical Systems and Model Reduction.

[BibT_eX]

[DOI]

CoRR, 2023

2022

Operator Inference for Quadratic Manifold Encodings.

[BibT_eX]

[DOI]

Dataset, September, 2022

Gramians, Energy Functionals, and Balanced Truncation for Linear Dynamical Systems With Quadratic Outputs.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2022

Generalized Quadratic-Embeddings for Nonlinear Dynamics using Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Neural ODEs with Irregular and Noisy Data.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Interpolation-Based Model Order Reduction for Polynomial Systems.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2021

Low-Dimensional Approximations of High-Dimensional Asset Price Models.

[BibT_eX]

[DOI]

Martin Redmann

Christian Bayer

SIAM J. Financial Math., 2021

Learning Low-Dimensional Quadratic-Embeddings of High-Fidelity Nonlinear Dynamics using Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Learning Dynamics from Noisy Measurements using Deep Learning with a Runge-Kutta Constraint.

[BibT_eX]

[DOI]

CoRR, 2021

A Greedy Data Collection Scheme For Linear Dynamical Systems.

[BibT_eX]

[DOI]

Karim Cherifi

CoRR, 2021

Discovery of Nonlinear Dynamical Systems using a Runge-Kutta Inspired Dictionary-based Sparse Regression Approach.

[BibT_eX]

[DOI]

CoRR, 2021

LQResNet: A Deep Neural Network Architecture for Learning Dynamic Processes.

[BibT_eX]

[DOI]

CoRR, 2021

2020

Identification of port-Hamiltonian systems from frequency response data.

[BibT_eX]

[DOI]

Paul Van Dooren

Syst. Control. Lett., 2020

Operator Inference and Physics-Informed Learning of Low-Dimensional Models for Incompressible Flows.

[BibT_eX]

[DOI]

CoRR, 2020

Data-Driven Learning of Reduced-order Dynamics for a Parametrized Shallow Water Equation.

[BibT_eX]

[DOI]

CoRR, 2020

A Non-Intrusive Method to Inferring Linear Port-Hamiltonian Realizations using Time-Domain Data.

[BibT_eX]

[DOI]

Karim Cherifi

CoRR, 2020

Low-Rank and Total Variation Regularization and Its Application to Image Recovery.

[BibT_eX]

[DOI]

Hussam Al Daas

CoRR, 2020

Operator inference for non-intrusive model reduction of systems with non-polynomial nonlinear terms.

[BibT_eX]

[DOI]

Boris Kramer

Benjamin Peherstorfer

Karen Willcox

CoRR, 2020

2019

Balanced Truncation for a Special Class of Bilinear Descriptor Systems.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2019

Identification of Dominant Subspaces for Linear Structured Parametric Systems and Model Reduction.

[BibT_eX]

[DOI]

CoRR, 2019

Data-Driven Identification of Rayleigh-Damped Second-Order Systems.

[BibT_eX]

[DOI]

CoRR, 2019

Time-limited H2-optimal model order reduction.

[BibT_eX]

[DOI]

Martin Redmann

Appl. Math. Comput., 2019

2018

H<sub>2</sub>-Quasi-Optimal Model Order Reduction for Quadratic-Bilinear Control Systems.

[BibT_eX]

[DOI]

Serkan Gugercin

SIAM J. Matrix Anal. Appl., 2018

2017

Krylov subspace-based model reduction for a class of bilinear descriptor systems.

[BibT_eX]

[DOI]

Mian Ilyas Ahmad

J. Comput. Appl. Math., 2017

POD-DEIM for efficient reduction of a dynamic 2D catalytic reactor model.

[BibT_eX]

[DOI]

Comput. Chem. Eng., 2017

2016

Multipoint interpolation of Volterra series and H<sub>2</sub>-model reduction for a family of bilinear descriptor systems.

[BibT_eX]

[DOI]

Syst. Control. Lett., 2016

2015

Model reduction of quadratic-bilinear descriptor systems via Carleman bilinearization.

[BibT_eX]

[DOI]

Mian Ilyas Ahmad