| Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks A Cini, I Marisca, C Alippi International Conference on Learning Representations (ICLR), 2022 | 116 | 2022 |
| Learning to reconstruct missing data from spatiotemporal graphs with sparse observations I Marisca, A Cini, C Alippi Advances in Neural Information Processing Systems (NeurIPS), 2022 | 48 | 2022 |
| Scalable spatiotemporal graph neural networks A Cini, I Marisca, FM Bianchi, C Alippi Proceedings of the AAAI conference on artificial intelligence 37 (6), 7218-7226, 2023 | 38 | 2023 |
| Cluster-based aggregate load forecasting with deep neural networks A Cini, S Lukovic, C Alippi 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 21 | 2020 |
| Graph neural networks for high-level synthesis design space exploration L Ferretti, A Cini, G Zacharopoulos, C Alippi, L Pozzi ACM Transactions on Design Automation of Electronic Systems 28 (2), 1-20, 2022 | 19* | 2022 |
| Torch Spatiotemporal A Cini, I Marisca GitHub. Accessed: Mar, 2022 | 19* | 2022 |
| Taming local effects in graph-based spatiotemporal forecasting A Cini, I Marisca, D Zambon, C Alippi Advances in Neural Information Processing Systems 36, 2024 | 17 | 2024 |
| Peak shaving in distribution networks using stationary energy storage systems: A Swiss case study NA Efkarpidis, S Imoscopi, M Geidl, A Cini, S Lukovic, C Alippi, I Herbst Sustainable Energy, Grids and Networks 34, 101018, 2023 | 16 | 2023 |
| Deep reinforcement learning with weighted Q-Learning A Cini, C D'Eramo, J Peters, C Alippi The Multi-disciplinary Conference on Reinforcement Learning and Decision …, 2022 | 14 | 2022 |
| Exploiting action-value uncertainty to drive exploration in reinforcement learning C D’Eramo, A Cini, M Restelli 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 14 | 2019 |
| Sparse graph learning from spatiotemporal time series A Cini, D Zambon, C Alippi Journal of Machine Learning Research 24 (242), 1-36, 2023 | 10 | 2023 |
| Graph deep learning for time series forecasting A Cini, I Marisca, D Zambon, C Alippi arXiv preprint arXiv:2310.15978, 2023 | 9 | 2023 |
| Gaussian approximation for bias reduction in Q-learning C D'Eramo, A Cini, A Nuara, M Pirotta, C Alippi, J Peters, M Restelli Journal of Machine Learning Research 22, 1-51, 2021 | 6 | 2021 |
| Spatio-temporal graph neural networks for aggregate load forecasting S Eandi, A Cini, S Lukovic, C Alippi 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 5 | 2022 |
| Graph-based Time Series Clustering for End-to-End Hierarchical Forecasting A Cini, D Mandic, C Alippi International Conference on Machine Learning (ICML), 2024 | 4 | 2024 |
| Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations G De Felice, A Cini, D Zambon, VV Gusev, C Alippi International Conference on Learning Representations (ICLR), 2024 | 3 | 2024 |
| Graph state-space models D Zambon, A Cini, L Livi, C Alippi arXiv preprint arXiv:2301.01741, 2023 | 3 | 2023 |
| Feudal graph reinforcement learning T Marzi, A Khehra, A Cini, C Alippi arXiv preprint arXiv:2304.05099, 2023 | 2 | 2023 |
| Object-Centric Relational Representations for Image Generation L Butera, A Cini, A Ferrante, C Alippi Transactions on Machine Learning Research, 2024 | | 2024 |
| Underactuated Attitude Control with Deep Reinforcement Learning M El Hariry, A Cini, A Balossino | | 2021 |
Cesare AlippiUniversitą della Svizzera italiana, Politecnico di MilanoVerified email at usi.ch
