| 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), 2021 | 108 | 2021 |
| 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 | 41 | 2022 |
| Scalable Spatiotemporal Graph Neural Networks A Cini, I Marisca, FM Bianchi, C Alippi Proceedings of the 37th AAAI Conference on Artificial Intelligence 37 (6 …, 2023 | 34 | 2023 |
| Torch Spatiotemporal, 3 2022 A Cini, I Marisca URL https://github. com/TorchSpatiotemporal/tsl 10, 0 | 14 | |
| Taming local effects in graph-based spatiotemporal forecasting A Cini, I Marisca, D Zambon, C Alippi Advances in Neural Information Processing Systems 36, 2024 | 12 | 2024 |
| Graph deep learning for time series forecasting A Cini, I Marisca, D Zambon, C Alippi arXiv preprint arXiv:2310.15978, 2023 | 8 | 2023 |
| Torch Spatiotemporal A Cini, I Marisca GitHub. Accessed: Mar, 2022 | 5 | 2022 |
| Graph-based forecasting with missing data through spatiotemporal downsampling I Marisca, C Alippi, FM Bianchi arXiv preprint arXiv:2402.10634, 2024 | 2 | 2024 |
| Driving exploration in online influence maximization with semi-bandit feedback I MARISCA Politecnico di Milano, 2018 | | 2018 |
Andrea CiniThe Swiss AI Lab IDSIA & USIVerified email at usi.ch
