Causal discovery with attention-based convolutional neural networks M Nauta, D Bucur, C Seifert Machine Learning and Knowledge Extraction 1 (1), 19, 2019 | 205 | 2019 |
Influence maximization in social networks with genetic algorithms D Bucur, G Iacca Applications of Evolutionary Computation: 19th European Conference …, 2016 | 95 | 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 |
Independent Prototype Propagation for Zero-Shot Compositionality F Ruis, G Burghouts, D Bucur Advances in Neural Information Processing Systems (NeurIPS 2021) 34 (2021), 2021 | 37 | 2021 |
Teaching Teaching & Understanding Understanding C Brabrand, J Andersen, D Bucur, R Thorbek | 34 | 2006 |
LIFT: learning fault trees from observational data M Nauta, D Bucur, M Stoelinga Quantitative Evaluation of Systems: 15th International Conference, QEST 2018 …, 2018 | 30 | 2018 |
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 | 30 | 2017 |
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 | 30 | 2013 |
Software verification for TinyOS D Bucur, MZ Kwiatkowska Proceedings of the 9th ACM/IEEE International Conference on Information …, 2010 | 28 | 2010 |
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 | 26 | 2016 |
Beyond ranking nodes: Predicting epidemic outbreak sizes by network centralities D Bucur, P Holme PLoS computational biology 16 (7), e1008052, 2020 | 25 | 2020 |
FFORT: a benchmark suite for fault tree analysis E Ruijters, CE Budde, MC Nakhaee, MIA Stoelinga, D Bucur, D Hiemstra, ... Singapore: Research Publishing, 2019 | 24 | 2019 |
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 | 22 | 2018 |
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 | 20 | 2019 |
Top influencers can be identified universally by combining classical centralities D Bucur Scientific reports 10 (1), 20550, 2020 | 19 | 2020 |
Temporal monitors for TinyOS D Bucur Runtime Verification: Third International Conference, RV 2012, Istanbul …, 2013 | 19 | 2013 |
Gender homophily in online book networks D Bucur Information sciences 481, 229-243, 2019 | 18 | 2019 |
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 |