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Jonas Soenen
Jonas Soenen
PhD Student, KU Leuven
Verified email at cs.kuleuven.be
Title
Cited by
Cited by
Year
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
252021
A scalable ensemble approach to forecast the electricity consumption of households
L Botman, J Soenen, K Theodorakos, A Yurtman, J Bekker, ...
IEEE Transactions on Smart Grid 14 (1), 757-768, 2022
122022
Scenario generation of residential electricity consumption through sampling of historical data
J Soenen, A Yurtman, T Becker, R D’hulst, K Vanthournout, W Meert, ...
Sustainable Energy, Grids and Networks 34, 100985, 2023
52023
Tackling noise in active semi-supervised clustering
J Soenen, S Dumančić, T Van Craenendonck, H Blockeel
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2020
22020
Semi-Supervised and Explainable Machine Learning with an Application to the Low-Voltage Grid
J Soenen
12023
Estimating Dynamic Time Warping Distance Between Time Series with Missing Data
A Yurtman, J Soenen, W Meert, H Blockeel
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023
2023
Measuring the Dissimilarity Between Time Series with Missing Data
A Yurtman, J Soenen, W Meert
Springer in the Lecture Notes in Computer Science Series (LNCS), 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
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