Anna Scampicchio

According to our database, Anna Scampicchio authored at least 20 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Goal-oriented safe active learning for predictive control using Bayesian recurrent neural networks.

Laura Boca de Giuli, Alessio La Bella, Manish Prajapat, Johannes Köhler, Anna Scampicchio, Riccardo Scattolini, Melanie Nicole Zeilinger

CoRR, April, 2026

Optimal uncertainty bounds for multivariate kernel regression under bounded noise: A Gaussian process-based dual function.

Amon Lahr, Anna Scampicchio, Johannes Köhler, Melanie N. Zeilinger

CoRR, March, 2026

2025

Physics-informed learning under mixing: How physical knowledge speeds up learning.

Anna Scampicchio, Leonardo F. Toso, Rahel Rickenbach, James Anderson, Melanie N. Zeilinger

CoRR, September, 2025

Gaussian processes for dynamics learning in model predictive control.

Anna Scampicchio, Elena Arcari, Amon Lahr, Melanie N. Zeilinger

Annu. Rev. Control., 2025

Optimal kernel regression bounds under energy-bounded noise.

Amon Lahr, Johannes Köhler, Anna Scampicchio, Melanie N. Zeilinger

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

Active Learning-Based Model Predictive Coverage Control.

Rahel Rickenbach, Johannes Köhler, Anna Scampicchio, Melanie N. Zeilinger, Andrea Carron

IEEE Trans. Autom. Control., September, 2024

Data-driven control of input-affine systems: the role of the signature transform.

Anna Scampicchio, Melanie N. Zeilinger

CoRR, 2024

Inverse optimal control as an errors-in-variables problem.

Rahel Rickenbach, Anna Scampicchio, Melanie N. Zeilinger

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

2023

Bayesian Multi-Task Learning MPC for Robotic Mobile Manipulation.

Elena Arcari, Maria Vittoria Minniti, Anna Scampicchio, Andrea Carron, Farbod Farshidian, Marco Hutter, Melanie N. Zeilinger

IEEE Robotics Autom. Lett., June, 2023

Kernel-based learning of orthogonal functions.

Anna Scampicchio, Mauro Bisiacco, Gianluigi Pillonetto

Neurocomputing, 2023

Error Analysis of Regularized Trigonometric Linear Regression With Unbounded Sampling: A Statistical Learning Viewpoint.

Anna Scampicchio, Elena Arcari, Melanie N. Zeilinger

IEEE Control. Syst. Lett., 2023

On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics.

Enea Monzio Compagnoni, Anna Scampicchio, Luca Biggio, Antonio Orvieto, Thomas Hofmann, Josef Teichmann

Proceedings of the International Joint Conference on Neural Networks, 2023

2022

Sample Complexity and Minimax Properties of Exponentially Stable Regularized Estimators.

Gianluigi Pillonetto, Anna Scampicchio

IEEE Trans. Autom. Control., 2022

Bayesian frequentist bounds for machine learning and system identification.

Giacomo Baggio, Algo Carè, Anna Scampicchio, Gianluigi Pillonetto

Autom., 2022

An update-and-design scheme for scenario-based LQR synthesis.

Anna Scampicchio, Andrea Iannelli

Proceedings of the American Control Conference, 2022

2021

Stable and robust LQR design via scenario approach.

Anna Scampicchio, Aleksandr Y. Aravkin, Gianluigi Pillonetto

Autom., 2021

Bayesian multi-task learning using finite-dimensional models: A comparative study.

Elena Arcari, Anna Scampicchio, Andrea Carron, Melanie N. Zeilinger

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

A convex approach to robust LQR.

Anna Scampicchio, Gianluigi Pillonetto

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

2019

Bayesian Kernel-Based Linear Control Design.

Anna Scampicchio, Alessandro Chiuso, Simone Formentin, Gianluigi Pillonetto

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018

A New Model Selection Approach to Hybrid Kernel-Based Estimation.

Anna Scampicchio, Gianluigi Pillonetto

Proceedings of the 57th IEEE Conference on Decision and Control, 2018