| Vessel pattern knowledge discovery from AIS data: A framework for anomaly detection and route prediction G Pallotta, M Vespe, K Bryan Entropy 15 (6), 2218-2245, 2013 | 754 | 2013 |
| Maritime anomaly detection: a review M Riveiro, G Pallotta, M Vespe WIRES Data Maning and Knowldge Dicsovery, 2018 | 168 | 2018 |
| Maritime traffic networks: From historical positioning data to unsupervised maritime traffic monitoring VF Arguedas, G Pallotta, M Vespe IEEE Transactions on Intelligent Transportation Systems 19 (3), 722-732, 2017 | 148 | 2017 |
| Human influence on the seasonal cycle of tropospheric temperature BD Santer, S Po-Chedley, MD Zelinka, I Cvijanovic, C Bonfils, PJ Durack, ... Science 361 (6399), eaas8806, 2018 | 135 | 2018 |
| Context-enhanced vessel prediction based on Ornstein-Uhlenbeck processes using historical AIS traffic patterns: Real-world experimental results G Pallotta, S Horn, P Braca, K Bryan 17th international conference on information fusion (FUSION), 1-7, 2014 | 97 | 2014 |
| Traffic knowledge discovery from AIS data G Pallotta, M Vespe, K Bryan Proceedings of the 16th International Conference on Information Fusion, 1996 …, 2013 | 87 | 2013 |
| Comparing tropospheric warming in climate models and satellite data BD Santer, S Solomon, G Pallotta, C Mears, S Po-Chedley, Q Fu, F Wentz, ... Journal of Climate 30 (1), 373-392, 2017 | 78 | 2017 |
| Causes of differences in model and satellite tropospheric warming rates BD Santer, JC Fyfe, G Pallotta, GM Flato, GA Meehl, MH England, ... Nature Geoscience 10 (7), 478-485, 2017 | 66 | 2017 |
| Automatic generation of geographical networks for maritime traffic surveillance VF Arguedas, G Pallotta, M Vespe 17th international conference on information fusion (FUSION), 1-8, 2014 | 48 | 2014 |
| Mining maritime vessel traffic: Promises, challenges, techniques L Cazzanti, G Pallotta OCEANS 2015-Genova, 1-6, 2015 | 45 | 2015 |
| Data-driven detection and context-based classification of maritime anomalies G Pallotta, AL Jousselme 2015 18th international conference on information fusion (fusion), 1152-1159, 2015 | 44 | 2015 |
| Quantifying stochastic uncertainty in detection time of human-caused climate signals BD Santer, JC Fyfe, S Solomon, JF Painter, C Bonfils, G Pallotta, ... Proceedings of the National Academy of Sciences 116 (40), 19821-19827, 2019 | 39 | 2019 |
| A new control chart for Weibull technological processes P Erto, G Pallotta Quality Technology & Quantitative Management 4 (4), 553-567, 2007 | 33 | 2007 |
| Robust evaluation of ENSO in climate models: How many ensemble members are needed? J Lee, YY Planton, PJ Gleckler, KR Sperber, E Guilyardi, AT Wittenberg, ... Geophysical Research Letters 48 (20), e2021GL095041, 2021 | 28 | 2021 |
| An example of data technology product: a control chart for Weibull processes P Erto, G Pallotta, SH Park International Statistical Review 76 (2), 157-166, 2008 | 27 | 2008 |
| Dissecting uncertainty-based fusion techniques for maritime anomaly detection AL Jousselme, G Pallotta 2015 18th International Conference on Information Fusion (Fusion), 34-41, 2015 | 22 | 2015 |
| Traffic route extraction and anomaly detection from AIS data G Pallotta, M Vespe, K Bryan International COST MOVE Workshop on Moving Objects at Sea, Brest, France, 1-4, 2013 | 21 | 2013 |
| The performance of semi-empirical Bayesian control charts for monitoring Weibull data P Erto, G Pallotta, P Biagio, CM Mastrangelo Quality Technology & Quantitative Management, 2017 | 19 | 2017 |
| Statistics for innovation P Erto, P Erto Springer Milan, 2009 | 18 | 2009 |
| Risk Game: Capturing impact of information quality on human belief assessment and decision making AL Jousselme, G Pallotta, J Locke International Journal of serious games 5 (4), 23-44, 2018 | 16 | 2018 |
