| Real-world anomaly detection by using digital twin systems and weakly supervised learning A Castellani, S Schmitt, S Squartini IEEE Transactions on Industrial Informatics 17 (7), 4733-4742, 2020 | 99 | 2020 |
| Task-sensitive concept drift detector with constraint embedding A Castellani, S Schmitt, B Hammer 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 01-08, 2021 | 11 | 2021 |
| Estimating the electrical power output of industrial devices with end-to-end time-series classification in the presence of label noise A Castellani, S Schmitt, B Hammer Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021 | 11 | 2021 |
| Stream-based active learning with verification latency in non-stationary environments A Castellani, S Schmitt, B Hammer International Conference on Artificial Neural Networks, 260-272, 2022 | 10 | 2022 |
| Method and system for semi-supervised deep anomaly detection for large-scale industrial monitoring systems based on time-series data utilizing digital twin simulation data S Schmitt, A Castellani, S Squartini US Patent App. 17/069,846, 2021 | 5 | 2021 |
| tfelm: a TensorFlow Toolbox for the Investigation of ELMs and MLPs Performance A Castellani, S Cornell, L Falaschetti, C Turchetti Proceedings on the International Conference on Artificial Intelligence (ICAI …, 2018 | 2 | 2018 |
| A multiband structure based on hammerstein model for nonlinear audio system identification A Terenzi, V Bruschi, S Cornell, A Castellani, S Cecchi 2019 11th International Symposium on Image and Signal Processing and …, 2019 | 1 | 2019 |
| Dealing with Inaccurate and Incomplete Labels in Industrial Streaming Data A Castellani | | 2024 |
| Analisi della risposta a creep di una lega da additive manufacturing A CASTELLANI | | 2019 |
| Analisi della risposta a creep di una lega da additive manufacturing S Spigarelli, A Castellani | | |
