| Data-driven control of complex networks G Baggio, DS Bassett, F Pasqualetti Nature communications 12 (1), 1-13, 2021 | 73 | 2021 |
| Stability conditions for cluster synchronization in networks of heterogeneous Kuramoto oscillators T Menara, G Baggio, DS Bassett, F Pasqualetti IEEE Transactions on Control of Network Systems 7 (1), 302-314, 2019 | 71 | 2019 |
| Data-Driven Minimum-Energy Controls for Linear Systems G Baggio, V Katewa, F Pasqualetti IEEE Control Systems Letters 3 (3), 589-594, 2019 | 66 | 2019 |
| On the role of network centrality in the controllability of complex networks N Bof, G Baggio, S Zampieri IEEE Transactions on Control of Network Systems 4 (3), 643-653, 2017 | 61 | 2017 |
| On the factorization of rational discrete-time spectral densities G Baggio, A Ferrante IEEE Transactions on Automatic Control 61 (4), 969-981, 2016 | 26 | 2016 |
| On the Existence of a Solution to a Spectral Estimation Problem à la Byrnes–Georgiou–Lindquist B Zhu, G Baggio IEEE Transactions on Automatic Control 64 (2), 820-825, 2019 | 25 | 2019 |
| A framework to control functional connectivity in the human brain T Menara, G Baggio, DS Bassett, F Pasqualetti 2019 IEEE 58th Conference on Decision and Control (CDC), 4697-4704, 2019 | 19 | 2019 |
| Efficient communication over complex dynamical networks: The role of matrix non-normality G Baggio, V Rutten, G Hennequin, S Zampieri Science Advances 6 (22), eaba2282, 2020 | 17 | 2020 |
| Functional control of oscillator networks T Menara, G Baggio, D Bassett, F Pasqualetti Nature Communications 13 (1), 1-13, 2022 | 13 | 2022 |
| Exact and approximate stability conditions for cluster synchronization of Kuramoto oscillators T Menara, G Baggio, DS Bassett, F Pasqualetti 2019 American Control Conference (ACC), 205-210, 2019 | 12 | 2019 |
| Quantum state preparation by controlled dissipation in finite time: From classical to quantum controllers G Baggio, F Ticozzi, L Viola 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 1072-1077, 2012 | 12 | 2012 |
| Further results on the convergence of the Pavon–Ferrante algorithm for spectral estimation G Baggio IEEE Transactions on Automatic Control 63 (10), 3510-3515, 2018 | 11 | 2018 |
| Parametrization of minimal spectral factors of discrete-time rational spectral densities G Baggio, A Ferrante IEEE Transactions on Automatic Control 64 (1), 396-403, 2019 | 10 | 2019 |
| On minimal spectral factors with zeroes and poles lying on prescribed regions G Baggio, A Ferrante IEEE Transactions on Automatic Control 61 (8), 2251-2255, 2016 | 10 | 2016 |
| Learning Minimum-Energy Controls from Heterogeneous Data G Baggio, F Pasqualetti 2020 American Control Conference (ACC), 3991-3996, 2020 | 9 | 2020 |
| Gramian Optimization with Input-Power Constraints G Baggio, S Zampieri, CW Scherer 2019 IEEE 58th Conference on Decision and Control (CDC), 5686-5691, 2019 | 8 | 2019 |
| Distributed Learning of Optimal Controls for Linear Systems F Celi, G Baggio, F Pasqualetti 2021 60th IEEE Conference on Decision and Control (CDC), 5771-5776, 2021 | 7 | 2021 |
| Conditions for Feedback Linearization of Network Systems T Menara, G Baggio, DS Bassett, F Pasqualetti IEEE Control Systems Letters 4 (3), 578-583, 2020 | 7 | 2020 |
| On the Relation Between Non-normality and Diameter in Linear Dynamical Networks G Baggio, S Zampieri 2018 European Control Conference (ECC), 1839-1844, 2018 | 6 | 2018 |
| Non-normality Improves Information Transmission Performance of Network Systems G Baggio, S Zampieri IEEE Transactions on Control of Network Systems 8 (4), 1846-1858, 2021 | 4 | 2021 |
Fabio PasqualettiProfessor, UC RiversideBestätigte E-Mail-Adresse bei engr.ucr.edu
