| Causal discovery with attention-based convolutional neural networks M Nauta, D Bucur, C Seifert Machine Learning and Knowledge Extraction 1 (1), 19, 2019 | 179 | 2019 |
| Influence maximization in social networks with genetic algorithms D Bucur, G Iacca Applications of Evolutionary Computation: 19th European Conference …, 2016 | 88 | 2016 |
| On software verification for sensor nodes D Bucur, M Kwiatkowska Journal of Systems and Software 84 (10), 1693–1707, 2011 | 48 | 2011 |
| A Survey of Formal Business Process VerificationFrom Soundness to Variability H Groefsema, D Bucur Third International Symposium on Business Modeling and Software Design 1 …, 2013 | 44 | 2013 |
| Teaching Teaching & Understanding Understanding C Brabrand, J Andersen, D Bucur, R Thorbek | 31 | 2006 |
| Independent Prototype Propagation for Zero-Shot Compositionality F Ruis, G Burghouts, D Bucur Advances in Neural Information Processing Systems (NeurIPS 2021) 34 (2021), 2021 | 29 | 2021 |
| LIFT: learning fault trees from observational data M Nauta, D Bucur, M Stoelinga Quantitative Evaluation of Systems: 15th International Conference, QEST 2018 …, 2018 | 29 | 2018 |
| Applying time series analysis and neighbourhood voting in a decentralised approach for fault detection and classification in WSNs TA Nguyen, D Bucur, M Aiello, K Tei Proceedings of the 4th Symposium on Information and Communication Technology …, 2013 | 29 | 2013 |
| Software verification for TinyOS D Bucur, MZ Kwiatkowska Proceedings of the 9th ACM/IEEE International Conference on Information …, 2010 | 28 | 2010 |
| Multi-objective evolutionary algorithms for influence maximization in social networks D Bucur, G Iacca, A Marcelli, G Squillero, A Tonda Applications of Evolutionary Computation: 20th European Conference …, 2017 | 26 | 2017 |
| Benchmark datasets for fault detection and classification in sensor data B De Bruijn, TA Nguyen, D Bucur, K Tei International Confererence on Sensor Networks, 185-195, 2016 | 24 | 2016 |
| Beyond ranking nodes: Predicting epidemic outbreak sizes by network centralities D Bucur, P Holme PLoS computational biology 16 (7), e1008052, 2020 | 22 | 2020 |
| Improving multi-objective evolutionary influence maximization in social networks D Bucur, G Iacca, A Marcelli, G Squillero, A Tonda Applications of Evolutionary Computation: 21st International Conference …, 2018 | 21 | 2018 |
| Temporal monitors for TinyOS D Bucur Runtime Verification: Third International Conference, RV 2012, Istanbul …, 2013 | 20 | 2013 |
| Fault trees from data: Efficient learning with an evolutionary algorithm A Linard, D Bucur, M Stoelinga Dependable Software Engineering. Theories, Tools, and Applications: 5th …, 2019 | 19 | 2019 |
| Top influencers can be identified universally by combining classical centralities D Bucur Scientific reports 10 (1), 20550, 2020 | 18 | 2020 |
| Secure data flow in a calculus for context awareness D Bucur, M Nielsen Concurrency, Graphs and Models, 439-456, 2008 | 18 | 2008 |
| Resource Discovery in Activity-Based Sensor Networks D Bucur, JE Bardram Mobile Networks and Applications, 2007, 2007 | 18 | 2007 |
| FFORT: a benchmark suite for fault tree analysis E Ruijters, CE Budde, MC Nakhaee, MIA Stoelinga, D Bucur, D Hiemstra, ... Singapore: Research Publishing, 2019 | 17 | 2019 |
| Optimizing groups of colluding strong attackers in mobile urban communication networks with evolutionary algorithms D Bucur, G Iacca, M Gaudesi, G Squillero, A Tonda Applied Soft Computing 40, 416-426, 2016 | 17 | 2016 |
Giovanni IaccaUniversity of TrentoVerified email at unitn.it
