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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
942018
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
542020
Transfer learning for time series anomaly detection
V Vercruyssen, W Meert, J Davis
ECML/PKDD Workshop on Interactive Adaptive Learning, 2017
402017
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
312020
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
302016
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
262020
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 Workshop on Outlier Detection and Description, 1-9, 2021
232021
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
142020
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
112022
A ranking stability measure for quantifying the robustness of anomaly detection methods
L Perini, C Galvin, V Vercruyssen
ECML PKDD 2020 Workshops: Workshops of the European Conference on Machine …, 2020
72020
Multi-domain active learning for semi-supervised anomaly detection
V Vercruyssen, L Perini, W Meert, J Davis
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022
62022
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
62019
“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
52020
Systematic evaluation of cash search strategies for unsupervised anomaly detection
I Antoniadis, V Vercruyssen, J Davis
Fourth International Workshop on Learning with Imbalanced Domains: Theory …, 2022
32022
Why are you weird? infusing interpretability in isolation forest for anomaly detection
NS Kartha, C Gautrais, V Vercruyssen
arXiv preprint arXiv:2112.06858, 2021
32021
Designing Anomaly Detection Algorithms that Exploit Flexible Supervision
V Vercruyssen
12020
Learning from Positive and Unlabeled Multi-Instance Bags in Anomaly Detection
L Perini, V Vercruyssen, J Davis
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
2023
AD-MERCS: Modeling Normality and Abnormality in Unsupervised Anomaly Detection
J Soenen, E Van Wolputte, V Vercruyssen, W Meert, H Blockeel
arXiv preprint arXiv:2305.12958, 2023
2023
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
Systeemdynamisch gedrag van gedistribueerde elektriciteitsopwekking
V Vercruyssen
Universiteit Antwerpen, 2014
2014
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