One of the main approaches to model reduction of both linear and nonlinear dynamical
systems is by means of interpolation. This approach seeks reduced models whose transfer …

Operator inference learns low-dimensional dynamical-system models with polynomial
nonlinear terms from trajectories of high-dimensional physical systems (non-intrusive model …

In this contribution we discuss the modeling and model reduction framework known as the
Loewner framework. This is a data-driven approach, applicable to large-scale systems …

In this work, we deal with the problem of approximating and equivalently formulating generic
nonlinear systems by means of specific classes thereof. Bilinear and quadratic-bilinear …

We propose a method for fitting quadratic-bilinear models from data. Although the dynamics
characterizing the original model consist of general analytic nonlinearities, we rely on lifting …

In this work, we address a model reduction problem in which the resulting reduced-order
model simultaneously matches sets of linear and nonlinear moments. We propose a …

This paper considers physical network systems where the energy storage is naturally
associated to the nodes of the graph, while the edges of the graph correspond to static …

Athanasios (Thanos) Antoulas was born in Athens, Greece. Having excelled at physics in
high school, he considered moving to England for his undergraduate studies. Counseled by …

In this work, we present a non-intrusive, ie, purely data-driven method that uses the Loewner
framework (LF) along with nonlinear optimization techniques to identify or reduce quadratic …

We propose a hybrid method based on the combination of computed-aided nonlinear
frequency response analysis with the Loewner framework, for the characterization of …