Deep Learning Approximation of Diffeomorphisms via Linear-Control Systems. - Alessandro Scagliotti (CoRR, 2021)

A piecewise conservative method for unconstrained convex optimization. - Alessandro Scagliotti; Piero Colli Franzone (Comput. Optim. Appl., 2022)

Losing momentum in continuous-time stochastic optimisation. - Kexin Jin; Jonas Latz; Chenguang Liu; Alessandro Scagliotti (CoRR, 2022)

A subgradient method with constant step-size for 𝓁1-composite optimization. - Alessandro Scagliotti; Piero Colli Franzone (CoRR, 2023)

From NeurODEs to AutoencODEs: a mean-field control framework for width-varying Neural Networks. - Cristina Cipriani; Massimo Fornasier; Alessandro Scagliotti (CoRR, 2023)

Normalizing flows as approximations of optimal transport maps via linear-control neural ODEs. - Alessandro Scagliotti; Sara Farinelli (CoRR, 2023)

A Minimax Optimal Control Approach for Robust Neural ODEs. - Cristina Cipriani; Alessandro Scagliotti; Tobias Wöhrer (ECC, 2024)

Minimax problems for ensembles of affine-control systems. - Alessandro Scagliotti (CoRR, 2024)

Approximation of Diffeomorphisms for Quantum State Transfers. - Eugenio Pozzoli; Alessandro Scagliotti (IEEE Control. Syst. Lett., 2025)

Minimax Problems for Ensembles of Control-Affine Systems. - Alessandro Scagliotti (SIAM J. Control. Optim., 2025)

Ensemble optimal control for managing drug resistance in cancer therapies. - Alessandro Scagliotti; Federico Scagliotti; Laura Deborah Locati; Federico Sottotetti (CoRR, 2025)

Shortest-path recovery from signature with an optimal control approach. - Marco Rauscher; Alessandro Scagliotti; Felipe Pagginelli Patricio (Math. Control. Signals Syst., 2025)