9 citations · 47 across the 37 of their papers we have counts for
7 papers · 1 filter
Barycentric rational approximation for learning the index of a dynamical system from limited data
Davide Pradovera, Ion Victor Gosea, Jan Heiland
We consider the task of data-driven identification of dynamical systems, specifically for systems whose behavior at large frequencies is non-standard, as encoded by a non-trivial r…
A non-intrusive data-based reformulation of a hybrid projection-based model reduction method
Ion Victor Gosea, Serkan Gugercin, Christopher Beattie
We present a novel data-driven reformulation of the iterative SVD-rational Krylov algorithm (ISRK), in its original formulation a Petrov-Galerkin (two-sided) projection-based itera…
Snapshot-driven Rational Interpolation of Parametric Systems
Art J. R. Pelling, Karim Cherifi, Ion Victor Gosea +1
Parametric data-driven modeling is relevant for many applications in which the model depends on parameters that can potentially vary in both space and time. In this paper, we prese…
optimal model reduction of linear systems with multiple quadratic outputs
Sean Reiter, Igor Pontes Duff, Ion Victor Gosea +1
In this work, we consider the optimal model reduction of dynamical systems that are linear in the state equation and up to quadratic nonlinearity in the output equation. As o…
On the Loewner framework, the Kolmogorov superposition theorem, and the curse of dimensionality
Athanasios C. Antoulas, Ion Victor Gosea, Charles Poussot-Vassal
The Loewner framework is an interpolatory approach for the approximation of linear and nonlinear systems. The purpose here is to extend this framework to linear parametric systems…
Learning reduced-order Quadratic-Linear models in Process Engineering using Operator Inference
Ion Victor Gosea, Luisa Peterson, Pawan Goyal +3
In this work, we address the challenge of efficiently modeling dynamical systems in process engineering. We use reduced-order model learning, specifically operator inference. This…
A modified AAA algorithm for learning stable reduced-order models from data
Tommaso Bradde, Stefano Grivet-Talocia, Quirin Aumann +1
In recent years, the Adaptive Antoulas-Anderson AAA algorithm has established itself as the method of choice for solving rational approximation problems. Data-driven Model Order Re…