| Deep learning models for wireless signal classification with distributed low-cost spectrum sensors S Rajendran, W Meert, D Giustiniano, V Lenders, S Pollin IEEE Transactions on Cognitive Communications and Networking 4 (3), 433-445, 2018 | 564 | 2018 |
| Range and coexistence analysis of long range unlicensed communication B Reynders, W Meert, S Pollin 2016 23rd International Conference on Telecommunications (ICT), 1-6, 2016 | 279 | 2016 |
| Lifted probabilistic inference by first-order knowledge compilation G Van den Broeck, N Taghipour, W Meert, J Davis, L De Raedt Proceedings ofthe 22th International Joint Conference on Artificial …, 2011 | 220 | 2011 |
| Power and spreading factor control in low power wide area networks B Reynders, W Meert, S Pollin 2017 IEEE International Conference on Communications (ICC), 1-6, 2017 | 199 | 2017 |
| SessionShield: Lightweight protection against session hijacking N Nikiforakis, W Meert, Y Younan, M Johns, W Joosen Engineering Secure Software and Systems: Third International Symposium …, 2011 | 127 | 2011 |
| A 90 nm CMOS, $6\{\upmu {\text {W}}} $ Power-Proportional Acoustic Sensing Frontend for Voice Activity Detection KMH Badami, S Lauwereins, W Meert, M Verhelst IEEE Journal of Solid-State Circuits 51 (1), 291-302, 2015 | 122 | 2015 |
| Skolemization for weighted first-order model counting G Van den Broeck, W Meert, A Darwiche, C Baral, GD Giacomo, T Eiter Proceedings of the 14th International Conference on Principles of Knowledge …, 2014 | 103 | 2014 |
| LS-SVM based spectral clustering and regression for predicting maintenance of industrial machines R Langone, C Alzate, B De Ketelaere, J Vlasselaer, W Meert, ... Engineering Applications of Artificial Intelligence 37, 268-278, 2015 | 95 | 2015 |
| Bitsquatting: Exploiting bit-flips for fun, or profit? N Nikiforakis, S Van Acker, W Meert, L Desmet, F Piessens, W Joosen Proceedings of the 22nd international conference on World Wide Web, 989-998, 2013 | 89 | 2013 |
| Semi-Supervised Anomaly Detection with an Application to Water Analytics. V Vercruyssen, W Meert, G Verbruggen, K Maes, R Baumer, J Davis ICDM 2018, 527-536, 2018 | 85 | 2018 |
| SAIFE: Unsupervised wireless spectrum anomaly detection with interpretable features S Rajendran, W Meert, V Lenders, S Pollin 2018 IEEE international symposium on dynamic spectrum access networks …, 2018 | 75 | 2018 |
| Unsupervised wireless spectrum anomaly detection with interpretable features S Rajendran, W Meert, V Lenders, S Pollin ieee transactions on cognitive communications and networking 5 (3), 637-647, 2019 | 66 | 2019 |
| Problog2: Probabilistic logic programming A Dries, A Kimmig, W Meert, J Renkens, G Van den Broeck, J Vlasselaer, ... Machine Learning and Knowledge Discovery in Databases: European Conference …, 2015 | 62 | 2015 |
| Fatigue prediction in outdoor runners via machine learning and sensor fusion T Op De Beéck, W Meert, K Schütte, B Vanwanseele, J Davis Proceedings of the 24th acm sigkdd international conference on knowledge …, 2018 | 55 | 2018 |
| Towards digesting the alphabet-soup of statistical relational learning L De Raedt, B Demoen, D Fierens, B Gutmann, G Janssens, A Kimmig, ... Proceedings of the 1st Workshop on Probabilistic Programming: Universal …, 2008 | 55 | 2008 |
| Machine learning with a reject option: A survey K Hendrickx, L Perini, D Van der Plas, W Meert, J Davis arXiv preprint arXiv:2107.11277, 2021 | 54 | 2021 |
| 24.2 Context-aware hierarchical information-sensing in a 6μW 90nm CMOS voice activity detector K Badami, S Lauwereins, W Meert, M Verhelst 2015 IEEE International Solid-State Circuits Conference-(ISSCC) Digest of …, 2015 | 54 | 2015 |
| Pattern-based anomaly detection in mixed-type time series L Feremans, V Vercruyssen, B Cule, W Meert, B Goethals Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020 | 51 | 2020 |
| Dtaidistance v2 W Meert, K Hendrickx, T Van Craenendonck, P Robberechts, H Blockeel, ... Zenodo (https://github.com/wannesm/dtaidistance), 2020 | 49* | 2020 |
| Learning ground CP-logic theories by leveraging Bayesian network learning techniques W Meert, J Struyf, H Blockeel Fundamenta Informaticae 89 (1), 131-160, 2008 | 49 | 2008 |
Jesse DavisProfessor, Department of Computer Science, KU LeuvenVerified email at cs.kuleuven.be
