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08/26/2023
Guaranteed Stable Quadratic Models and their applications in SINDy and Operator Inference
Scientific machine learning for learning dynamical systems is a powerful...
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01/24/2023
Inference of Continuous Linear Systems from Data with Guaranteed Stability
Machine-learning technologies for learning dynamical systems from data p...
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01/23/2023
Dominant Subspaces of High-Fidelity Nonlinear Structured Parametric Dynamical Systems and Model Reduction
In this work, we investigate a model order reduction scheme for high-fid...
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07/09/2021
Model order reduction for bilinear systems with non-zero initial states – different approaches with error bounds
In this paper, we consider model order reduction for bilinear systems wi...
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02/15/2021
Full state approximation by Galerkin projection reduced order models for stochastic and bilinear systems
In this paper, the problem of full state approximation by model reductio...
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10/13/2020
Operator Inference and Physics-Informed Learning of Low-Dimensional Models for Incompressible Flows
Reduced-order modeling has a long tradition in computational fluid dynam...
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03/13/2020
Toward fitting structured nonlinear systems by means of dynamic mode decomposition
The dynamic mode decomposition (DMD) is a data-driven method used for id...
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10/30/2019
Identification of Dominant Subspaces for Linear Structured Parametric Systems and Model Reduction
In this paper, we discuss a novel model reduction framework for generali...
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10/02/2019
Data-Driven Identification of Rayleigh-Damped Second-Order Systems
In this paper, we present a data-driven approach to identify second-orde...
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09/10/2019