Author

Guillaume O. Berger

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Preprint Aug 2026

Data-driven Koopman mode approximation: A neural power iteration algorithm

A novel data-driven algorithm to approximate the dominant eigenfunctions of the Koopman operator of nonlinear dynamical systems using neural networks using neural networks to fight the curse of dimensionality arising from using expressive templates for the mode approximation.

Guillaume O. Berger, Raphael M. Jungers · 0 citations

Preprint Aug 2026

Direct vs. Indirect Data-Driven Control: Case-study of Switching Systems Stability

This paper provides a novel framework for the stability analysis of switched linear systems from noisy state measurements, using the indirect approach and quadratic Lyapunov analysis and combines generalization bounds from machine learning and system identification with sensitivity analysis from quadratic Lyapunov analysis.

Alexis Vuille, Guillaume O. Berger, Raphael M. Jungers · 0 citations