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Vincent Vercruyssen
Vincent Vercruyssen
Verified email at cs.kuleuven.be - Homepage
Title
Cited by
Cited by
Year
Semi-supervised Anomaly Detection with an Application to Water Analytics
V Vercruyssen, W Meert, G Verbruggen, K Maes, R Bäumer, J Davis
IEEE International Conference on Data Mining (ICDM), 527-536, 2018
612018
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
372019
Transfer learning for time series anomaly detection
V Vercruyssen, W Meert, J Davis
ECML/PKDD Workshop on Interactive Adaptive Learning, 2017
272017
Qualitative spatial reasoning for soccer pass prediction
V Vercruyssen, L De Raedt, J Davis
ECML/PKDD Workshop on Machine Learning and Data Mining for Sports Analytics, 2016
272016
Transfer learning for anomaly detection through localized and unsupervised instance selection
V Vincent, M Wannes, D Jesse
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 6054-6061, 2020
122020
Quantifying the confidence of anomaly detectors in their example-wise predictions
L Perini, V Vercruyssen, J Davis
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2020
92020
The effect of hyperparameter tuning on the comparative evaluation of unsupervised anomaly detection methods
J Soenen, E Van Wolputte, L Perini, V Vercruyssen, W Meert, J Davis, ...
Proceedings of the KDD 21, 1-9, 2021
52021
Class prior estimation in active positive and unlabeled learning
L Perini, V Vercruyssen, J Davis
Proceedings of the 29th International Joint Conference on Artificial …, 2020
52020
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
ECML/PKDD, 2019
42019
A Ranking Stability Measure for Quantifying the Robustness of Anomaly Detection Methods
L Perini, C Galvin, V Vercruyssen
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2020
32020
“Now you see it, now you don't!” Detecting Suspicious Pattern Absences in Continuous Time Series
V Vercruyssen, W Meert, J Davis
Proceedings of the 2020 SIAM international conference on data mining, 127-135, 2020
32020
Transferring the Contamination Factor between Anomaly Detection Domains by Shape Similarity
L Perini, V Vercruyssen, J Davis
Proceedings of the AAAI Conference on Artificial Intelligence 36 (4), 4128-4136, 2022
12022
Why Are You Weird? Infusing Interpretability in Isolation Forest for Anomaly Detection
NS Kartha, C Gautrais, V Vercruyssen
arXiv preprint arXiv:2112.06858, 2021
2021
Why Are You Weird? Infusing Interpretability in Isolation Forest for Anomaly Detection
N Sobha Kartha, C Gautrais, V Vercruyssen
arXiv e-prints, arXiv: 2112.06858, 2021
2021
Why Are You Weird? Infusing Interpretability in Isolation Forest for Anomaly Detection
V Vercruyssen, C Gautrais, N Sobha Kartha
Proceedings for the Explainable Agency in AI Workshop at the 35th AAAI …, 2021
2021
Designing Anomaly Detection Algorithms that Exploit Flexible Supervision
V Vercruyssen
2020
Systeemdynamisch gedrag van gedistribueerde elektriciteitsopwekking
V Vercruyssen
Universiteit Antwerpen, 2014
2014
Multi-domain Active Learning for Semi-supervised Anomaly Detection
V Vercruyssen, L Perini, W Meert, J Davis
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