Quantum state preparation by controlled dissipation in finite time: From classical to quantum controllers. - Giacomo Baggio; Francesco Ticozzi; Lorenza Viola (CDC, 2012)

On the Factorization of Rational Discrete-Time Spectral Densities. - Giacomo Baggio; Augusto Ferrante (IEEE Trans. Autom. Control., 2016)

On Minimal Spectral Factors With Zeroes and Poles Lying on Prescribed Regions. - Giacomo Baggio; Augusto Ferrante (IEEE Trans. Autom. Control., 2016)

LTI Stochastic Processes: a Behavioral Perspective. - Giacomo Baggio; Rodolphe Sepulchre (CoRR, 2017)

On the Role of Network Centrality in the Controllability of Complex Networks. - Nicoletta Bof; Giacomo Baggio; Sandro Zampieri (IEEE Trans. Control. Netw. Syst., 2017)

Information Transmission in Dynamical Networks: The Normal Network Case. - Giacomo Baggio; Virginia Rutten; Guillaume Hennequin; Sandro Zampieri (CDC, 2018)

On the Relation Between Non-normality and Diameter in Linear Dynamical Networks. - Giacomo Baggio; Sandro Zampieri (ECC, 2018)

Improving Consensus-Based Distributed Camera Calibration Via Edge Pruning and Graph Traversal Initialization. - Giulia Michieletto; Simone Milani; Angelo Cenedese; Giacomo Baggio (ICASSP, 2018)

Stability Conditions for Cluster Synchronization in Networks of Kuramoto Oscillators. - Tommaso Menara; Giacomo Baggio; Danielle S. Bassett; Fabio Pasqualetti (CoRR, 2018)

Further Results on the Convergence of the Pavon-Ferrante Algorithm for Spectral Estimation. - Giacomo Baggio (IEEE Trans. Autom. Control., 2018)

Exact and Approximate Stability Conditions for Cluster Synchronization of Kuramoto Oscillators. - Tommaso Menara; Giacomo Baggio; Danielle S. Bassett; Fabio Pasqualetti (ACC, 2019)

Gramian Optimization with Input-Power Constraints. - Giacomo Baggio; Sandro Zampieri; Carsten W. Scherer (CDC, 2019)

A Framework to Control Functional Connectivity in the Human Brain. - Tommaso Menara; Giacomo Baggio; Danielle S. Bassett; Fabio Pasqualetti (CDC, 2019)

Quantum Information Encoding from Stabilizing Dynamics. - Francesco Ticozzi; Giacomo Baggio; Lorenza Viola (CDC, 2019)

The Shannon Capacity of Linear Dynamical Networks. - Giacomo Baggio; Vaibhav Katewa; Fabio Pasqualetti; Sandro Zampieri (ECC, 2019)

Data-driven Learning of Minimum-Energy Controls for Linear Systems. - Giacomo Baggio; Vaibhav Katewa; Fabio Pasqualetti (CoRR, 2019)

Efficient Communication over Complex Dynamical Networks. - Giacomo Baggio; Virginia Rutten; Guillaume Hennequin; Sandro Zampieri (CoRR, 2019)

Data-Driven Minimum-Energy Controls for Linear Systems. - Giacomo Baggio; Vaibhav Katewa; Fabio Pasqualetti (IEEE Control. Syst. Lett., 2019)

Parametrization of Minimal Spectral Factors of Discrete-Time Rational Spectral Densities. - Giacomo Baggio; Augusto Ferrante (IEEE Trans. Autom. Control., 2019)

Conal Distances Between Rational Spectral Densities. - Giacomo Baggio; Augusto Ferrante; Rodolphe Sepulchre (IEEE Trans. Autom. Control., 2019)

On the Existence of a Solution to a Spectral Estimation Problem à la Byrnes-Georgiou-Lindquist. - Bin Zhu 014; Giacomo Baggio (IEEE Trans. Autom. Control., 2019)

Learning Minimum-Energy Controls from Heterogeneous Data. - Giacomo Baggio; Fabio Pasqualetti (ACC, 2020)

Data-Driven Control of Complex Networks. - Giacomo Baggio; Danielle S. Bassett; Fabio Pasqualetti (CoRR, 2020)

Conditions for Feedback Linearization of Network Systems. - Tommaso Menara; Giacomo Baggio; Danielle S. Bassett; Fabio Pasqualetti (IEEE Control. Syst. Lett., 2020)

Stability Conditions for Cluster Synchronization in Networks of Heterogeneous Kuramoto Oscillators. - Tommaso Menara; Giacomo Baggio; Danielle S. Bassett; Fabio Pasqualetti (IEEE Trans. Control. Netw. Syst., 2020)

Distributed Learning of Optimal Controls for Linear Systems. - Federico Celi; Giacomo Baggio; Fabio Pasqualetti (CDC, 2021)

Dissipative encoding of quantum information. - Giacomo Baggio; Francesco Ticozzi; Peter D. Johnson 002; Lorenza Viola (Quantum Inf. Comput., 2021)

Non-normality Improves Information Transmission Performance of Network Systems. - Giacomo Baggio; Sandro Zampieri (IEEE Trans. Control. Netw. Syst., 2021)

Finite-Sample Guarantees for State-Space System Identification Under Full State Measurements. - Giacomo Baggio; Algo Carè; Gianluigi Pillonetto (CDC, 2022)

Reachable Volume of Large-Scale Linear Network Systems: The Single-Input Case. - Giacomo Baggio; Sandro Zampieri (CDC, 2022)

Closed-form Estimates of the LQR Gain From Finite Data. - Federico Celi; Giacomo Baggio; Fabio Pasqualetti (CDC, 2022)

Energy-Aware Controllability of Complex Networks. - Giacomo Baggio; Fabio Pasqualetti; Sandro Zampieri (Annu. Rev. Control. Robotics Auton. Syst., 2022)

Bayesian frequentist bounds for machine learning and system identification. - Giacomo Baggio; Algo Carè; Anna Scampicchio; Gianluigi Pillonetto (Autom., 2022)

Dynamic Brain Networks with Prescribed Functional Connectivity. - Umberto Casti; Giacomo Baggio; Danilo Benozzo; Sandro Zampieri; Alessandra Bertoldo; Alessandro Chiuso (CDC, 2023)

Data-Driven Eigenstructure Assignment for Sparse Feedback Design. - Federico Celi; Giacomo Baggio; Fabio Pasqualetti (CDC, 2023)

Closed-form and robust expressions for data-driven LQ control. - Federico Celi; Giacomo Baggio; Fabio Pasqualetti (Annu. Rev. Control., 2023)

On the capacity of continuous-time Hopfield models. - Simone Betteti; Giacomo Baggio; Sandro Zampieri (CDC, 2024)

Exploring the Impact of Memory on Network Controllability. - Marco Peruzzo; Giacomo Baggio; Francesco Ticozzi (ECC, 2024)

The Bayesian Separation Principle for Data-driven Control. - Riccardo Alessandro Grimaldi; Giacomo Baggio; Ruggero Carli; Gianluigi Pillonetto (CoRR, 2024)

Input-Driven Dynamics for Robust Memory Retrieval in Hopfield Networks. - Simone Betteti; Giacomo Baggio; Francesco Bullo; Sandro Zampieri (CoRR, 2024)

Firing Rate Models as Associative Memory: Excitatory-Inhibitory Balance for Robust Retrieval. - Simone Betteti; Giacomo Baggio; Francesco Bullo; Sandro Zampieri (CoRR, 2024)

Controllability of Large-Scale Networks: The Control Energy Exponents. - Giacomo Baggio; Sandro Zampieri (IEEE Trans. Control. Netw. Syst., 2024)

How Complex is a Complex Network? Insights From Linear Systems Theory. - Giacomo Baggio; Marco Fabris (IEEE Control. Syst. Lett., 2025)

Controllable Neural Architectures for Multi-Task Control. - Umberto Casti; Giacomo Baggio; Sandro Zampieri; Fabio Pasqualetti (CoRR, 2025)

Finding Conditions for Target Controllability under Christmas Trees. - Marco Peruzzo; Giacomo Baggio; Francesco Ticozzi (CoRR, 2025)

Obtaining Structural Network Controllability with Higher-Order Local Dynamics. - Marco Peruzzo; Giacomo Baggio; Francesco Ticozzi (CoRR, 2025)