Следене
Kilian Hendrickx
Kilian Hendrickx
Потвърден имейл адрес: cs.kuleuven.be - Начална страница
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Позовавания
Година
Machine learning with a reject option: A survey
K Hendrickx, L Perini, D Van der Plas, W Meert, J Davis
Machine Learning, 1-38, 2024
722024
A general anomaly detection framework for fleet-based condition monitoring of machines
K Hendrickx, W Meert, Y Mollet, J Gyselinck, B Cornelis, K Gryllias, ...
Mechanical Systems and Signal Processing 139 (May 2020), 2019
502019
wannesm/dtaidistance v2. 0.0
W Meert, K Hendrickx, TV Craenendonck
Zenodo, 2020
332020
TSFuse: Automated feature construction for multiple time series data
A De Brabandere, T Op De Beéck, K Hendrickx, W Meert, J Davis
Machine Learning, 1-56, 2022
102022
Condition monitoring of gears under medium rotational speed
A Mauricio, C Freitas, J Cuenca, B Cornelis, K Janssens, K Hendrickx, ...
24th International Congress on Sound and Vibration, 8, 2017
72017
A fleet-wide approach for condition monitoring of similar machines using time-series clustering
K Hendrickx, W Meert, B Cornelis, K Janssens, K Gryllias, J Davis
Advances in Condition Monitoring of Machinery in Non-Stationary Operations …, 2019
42019
Know Your Limits: Machine Learning with Rejection for Vehicle Engineering
K Hendrickx, W Meert, B Cornelis, J Davis
International Conference on Advanced Data Mining and Applications, 273-288, 2022
22022
Similarity-based anomaly score for fleet-based condition monitoring
K Hendrickx, W Meert, B Cornelis, K Gryllias, J Davis
Proceedings of the Annual Conference of the Prognostics and Health …, 2020
22020
Fleet-based health monitoring for end-of-production-line and operational testing
K Hendrickx, W Meert, JPDC Patricio, B Cornelis, K Gryllias, J Davis
Online Proceedings of ISMA2020, 2020
22020
Customer-correlated drive cycle generation for realistic fuel consumption and driving emissions testing
B Cornelis, K Hendrickx, D Hoffmann, M Horst, M Vollbrecht, M Kienert
JSAE Annual Congres 2019, 2019
12019
Analyzing scarce sensor data with applications in fleet-based anomaly detection and learning to reject
K Hendrickx
2022
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