| Process mining manifesto W Van Der Aalst, A Adriansyah, AKA De Medeiros, F Arcieri, T Baier, ... Business Process Management Workshops: BPM 2011 International Workshops …, 2012 | 1960 | 2012 |
| Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo’ E Lavezzo, E Franchin, C Ciavarella, G Cuomo-Dannenburg, L Barzon, ... Nature 584 (7821), 425-429, 2020 | 1380* | 2020 |
| Supervised neural networks for the classification of structures A Sperduti, A Starita IEEE transactions on neural networks 8 (3), 714-735, 1997 | 962 | 1997 |
| A general framework for adaptive processing of data structures P Frasconi, M Gori, A Sperduti IEEE transactions on Neural Networks 9 (5), 768-786, 1998 | 655 | 1998 |
| A self-organizing map for adaptive processing of structured data M Hagenbuchner, A Sperduti, AC Tsoi IEEE transactions on Neural Networks 14 (3), 491-505, 2003 | 244 | 2003 |
| Conformance checking based on multi-perspective declarative process models A Burattin, FM Maggi, A Sperduti Expert systems with applications 65, 194-211, 2016 | 217 | 2016 |
| Time and activity sequence prediction of business process instances M Polato, A Sperduti, A Burattin, M Leoni Computing 100, 1005-1031, 2018 | 205 | 2018 |
| Speed up learning and network optimization with extended back propagation A Sperduti, A Starita Neural networks 6 (3), 365-383, 1993 | 184 | 1993 |
| Recursive self-organizing network models B Hammer, A Micheli, A Sperduti, M Strickert Neural Networks 17 (8-9), 1061-1085, 2004 | 171 | 2004 |
| ANASTASIA: ANdroid mAlware detection using STatic analySIs of Applications H Fereidooni, M Conti, D Yao, A Sperduti 2016 8th IFIP international conference on new technologies, mobility and …, 2016 | 157 | 2016 |
| Encoding labeled graphs by labeling RAAM A Sperduti Advances in Neural Information Processing Systems 6, 1993 | 148 | 1993 |
| A general framework for unsupervised processing of structured data B Hammer, A Micheli, A Sperduti, M Strickert Neurocomputing 57, 3-35, 2004 | 133 | 2004 |
| LSTM networks for data-aware remaining time prediction of business process instances N Navarin, B Vincenzi, M Polato, A Sperduti 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1-7, 2017 | 132 | 2017 |
| Data-aware remaining time prediction of business process instances M Polato, A Sperduti, A Burattin, M de Leoni 2014 International Joint Conference on Neural Networks (IJCNN), 816-823, 2014 | 124 | 2014 |
| Application of cascade correlation networks for structures to chemistry AM Bianucci, A Micheli, A Sperduti, A Starita Applied Intelligence 12, 117-147, 2000 | 121 | 2000 |
| PLG: A framework for the generation of business process models and their execution logs A Burattin, A Sperduti Business Process Management Workshops: BPM 2010 International Workshops and …, 2011 | 117 | 2011 |
| An improved boosting algorithm and its application to text categorization F Sebastiani, A Sperduti, N Valdambrini Proceedings of the ninth international conference on Information and …, 2000 | 116 | 2000 |
| Multiclass classification with multi-prototype support vector machines F Aiolli, A Sperduti Journal of Machine Learning Research 6, 817-850, 2005 | 104 | 2005 |
| Analysis of the internal representations developed by neural networks for structures applied to quantitative structure− activity relationship studies of benzodiazepines A Micheli, A Sperduti, A Starita, AM Bianucci Journal of Chemical Information and Computer Sciences 41 (1), 202-218, 2001 | 104 | 2001 |
| Challenges in Deep Learning. P Angelov, A Sperduti ESANN, 2016 | 97 | 2016 |