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20232026
most citedFrom system models to class models: An in-context learning paradigm

17 citations · 32 across the 20 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

eess.SY2024

One controller to rule them all

Riccardo Busetto, Valentina Breschi, Marco Forgione +2

Imagine having a system to control and only know that it belongs to a certain class of dynamical systems. Would it not be amazing to simply plug in a controller and have it work as…

eess.SY2024★ 2 cited

Bias correction and instrumental variables for direct data-driven model-reference control

Manas Mejari, Valentina Breschi, Simone Formentin +1

Managing noisy data is a central challenge in direct data-driven control design. We propose an approach for synthesizing model-reference controllers for linear time-invariant (LTI)…

cs.LG2024

Enhanced Transformer architecture for in-context learning of dynamical systems

Matteo Rufolo, Dario Piga, Gabriele Maroni +1

Recently introduced by some of the authors, the in-context identification paradigm aims at estimating, offline and based on synthetic data, a meta-model that describes the behavior…

cs.LG2024★ 1 cited

Model order reduction of deep structured state-space models: A system-theoretic approach

Marco Forgione, Manas Mejari, Dario Piga

With a specific emphasis on control design objectives, achieving accurate system modeling with limited complexity is crucial in parametric system identification. The recently intro…

cs.LG2024

Synthetic data generation for system identification: leveraging knowledge transfer from similar systems

Dario Piga, Matteo Rufolo, Gabriele Maroni +2

This paper addresses the challenge of overfitting in the learning of dynamical systems by introducing a novel approach for the generation of synthetic data, aimed at enhancing mode…