| Pattern-based anomaly detection in mixed-type time series L Feremans, V Vercruyssen, B Cule, W Meert, B Goethals Joint European conference on machine learning and knowledge discovery in …, 2019 | 36 | 2019 |
| Mining Top-k Quantile-based Cohesive Sequential Patterns L Feremans, B Cule, B Goethals Proceedings of the 2018 SIAM international conference on data mining, 90-98, 2018 | 10 | 2018 |
| Combining Instance and Feature neighbors for Efficient Multi-label Classification L Feremans, B Cule, C Vens, B Goethals 2017 IEEE International Conference on Data Science and Advanced Analytics …, 2017 | 8* | 2017 |
| Efficient discovery of sets of co-occurring items in event sequences B Cule, L Feremans, B Goethals Joint European Conference on Machine Learning and Knowledge Discovery in …, 2016 | 8 | 2016 |
| Pattern mining for learning typical turbine response during dynamic wind turbine events L Feremans, B Cule, C Devriendt, B Goethals, J Helsen International Design Engineering Technical Conferences and Computers and …, 2017 | 7 | 2017 |
| Efficiently mining cohesion-based patterns and rules in event sequences B Cule, L Feremans, B Goethals Data Mining and Knowledge Discovery 33 (4), 1125-1182, 2019 | 5 | 2019 |
| A framework for pattern mining and anomaly detection in multi-dimensional time series and event logs L Feremans, V Vercruyssen, W Meert, B Cule, B Goethals International Workshop on New Frontiers in Mining Complex Patterns, 3-20, 2019 | 4 | 2019 |
| Aspect-Oriented Refactoring L Feremans MS Thesis. Vrije Universiteit Brussel, 2005 | 3 | 2005 |
| Fleet-oriented pattern mining combined with time series signature extraction for understanding of wind farm response to storm conditions PJ Daems, L Feremans, T Verstraeten, B Cule, B Goethals, J Helsen Advances in Condition Monitoring and Structural Health Monitoring, 271-283, 2021 | 2 | 2021 |
| PETSC: pattern-based embedding for time series classification L Feremans, B Cule, B Goethals Data Mining and Knowledge Discovery 36 (3), 1015-1061, 2022 | 1 | 2022 |
| Mining Cohesive Patterns in Sequences and Extreme Multi-label Classification: Proefschrift L Feremans | | 2020 |
| Mining Cohesive Patterns in Sequences and Extreme Multi-label Classification L Feremans University of Antwerp, 2020 | | 2020 |
Boris ČuleTilburg UniversityVerified email at tilburguniversity.edu
