| Bayesian multi-task learning mpc for robotic mobile manipulation E Arcari, MV Minniti, A Scampicchio, A Carron, F Farshidian, M Hutter, ... IEEE Robotics and Automation Letters 8 (6), 3222-3229, 2023 | 30 | 2023 |
| Stable and robust LQR design via scenario approach A Scampicchio, A Aravkin, G Pillonetto Automatica 129, 109571, 2021 | 21 | 2021 |
| On the effectiveness of randomized signatures as reservoir for learning rough dynamics EM Compagnoni, A Scampicchio, L Biggio, A Orvieto, T Hofmann, ... 2023 International Joint Conference on Neural Networks (IJCNN), 1-8, 2023 | 15 | 2023 |
| Bayesian frequentist bounds for machine learning and system identification G Baggio, A Carè, A Scampicchio, G Pillonetto Automatica 146, 110599, 2022 | 14 | 2022 |
| Sample complexity and minimax properties of exponentially stable regularized estimators G Pillonetto, A Scampicchio IEEE Transactions on Automatic Control 67 (5), 2330-2342, 2021 | 12 | 2021 |
| Bayesian kernel-based linear control design A Scampicchio, A Chiuso, S Formentin, G Pillonetto 2019 IEEE 58th conference on decision and control (CDC), 822-827, 2019 | 11 | 2019 |
| Nonlinear hybrid systems identification using kernel-based techniques A Scampicchio, A Giaretta, G Pillonetto IFAC-PapersOnLine 51 (15), 269-274, 2018 | 11 | 2018 |
| Active learning-based model predictive coverage control R Rickenbach, J Köhler, A Scampicchio, MN Zeilinger, A Carron IEEE Transactions on Automatic Control, 2024 | 8 | 2024 |
| Bayesian multi-task learning using finite-dimensional models: A comparative study E Arcari, A Scampicchio, A Carron, MN Zeilinger 2021 60th IEEE Conference on Decision and Control (CDC), 2218-2225, 2021 | 5 | 2021 |
| A new model selection approach to hybrid kernel-based estimation A Scampicchio, G Pillonetto 2018 IEEE Conference on Decision and Control (CDC), 3068-3073, 2018 | 4 | 2018 |
| A convex approach to robust LQR A Scampicchio, G Pillonetto 2020 59th IEEE Conference on Decision and Control (CDC), 3705-3710, 2020 | 3 | 2020 |
| LQR design under stability constraints A Scampicchio, A Aravkin, G Pillonetto IFAC-PapersOnLine 53 (2), 5556-5560, 2020 | 3 | 2020 |
| Kernel-based learning of orthogonal functions A Scampicchio, M Bisiacco, G Pillonetto Neurocomputing 545, 126237, 2023 | 2 | 2023 |
| Error analysis of regularized trigonometric linear regression with unbounded sampling: a statistical learning viewpoint A Scampicchio, E Arcari, MN Zeilinger IEEE Control Systems Letters, 2023 | 2 | 2023 |
| Assessment of the Fractal Dimension of Images Derived by Biopsy of Pancreatic Tissue: Implications for Tumor Diagnosis A Scampicchio, A Tura, S Sbrignadello, F Grizzi, S Fiorino, S Blandamura, ... XIV Mediterranean Conference on Medical and Biological Engineering and …, 2016 | 2 | 2016 |
| A Markov Chain Monte Carlo approach for Pseudo-Input selection in Sparse Gaussian Processes A Scampicchio, S Chandrasekaran, MN Zeilinger IFAC-PapersOnLine 56 (2), 10515-10520, 2023 | 1 | 2023 |
| An update-and-design scheme for scenario-based LQR synthesis A Scampicchio, A Iannelli 2022 American Control Conference (ACC), 932-939, 2022 | 1 | 2022 |
| Gaussian processes for dynamics learning in model predictive control A Scampicchio, E Arcari, A Lahr, MN Zeilinger arXiv preprint arXiv:2502.02310, 2025 | | 2025 |
| Data-driven control of input-affine systems: the role of the signature transform A Scampicchio, MN Zeilinger arXiv preprint arXiv:2409.05685, 2024 | | 2024 |
| Inverse optimal control as an errors-in-variables problem R Rickenbach, A Scampicchio, MN Zeilinger 6th Annual Learning for Dynamics & Control Conference, 375-386, 2024 | | 2024 |
Gianluigi PillonettoProfessor of Automatic Control, University of PadovaEmail verificata su dei.unipd.it