Publications

2026

Louis Carpentier, Laurens Devos, Wannes Meert and Mathias Verbeke. “HydraAD: Exceptionally fast and accurate time series anomaly detection using competing random kernels.” Data Mining And Knowledge Discovery. code

Louis Carpentier, Laurens Devos, Wannes Meert and Mathias Verbeke. “SubTSMD: discovering subspace motifs with temporal variations in multivariate time series.” Data Mining And Knowledge Discovery. code

Louis Carpentier, Wannes Meert and Mathias Verbeke. “InTimeAD: Interactive Time Series Anomaly Detection.” Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), doi: 10.1609/aaai.v40i48.42336. paper code movie movie

Xiaokum Zhu, Louis Carpentier and Mathias Verbeke. “When Foundation Models are One-Liners: Limitations and Future Directions for Time Series Anomaly Detection.” Proceedings of the International Conference on Learning Representations (ICLR). paper code

2025

Louis Carpentier, Nick Seeuws, Wannes Meert and Mathias Verbeke. “dtaianomaly: A Python library for time series anomaly detection” arXiv: 2208.14921 . preprint code

2024

Louis Carpentier, Len Feremans, Wannes Meert and Mathias Verbeke. “Pattern-based Time Series Semantic Segmentation with Gradual State Transitions.” Proceedings of the 2024 SIAM International Conference on Data Mining (SDM), doi: 10.1137/1.9781611978032.36. paper code

Louis Carpentier, Arne De Temmerman and Mathias Verbeke. “Towards contextual, cost-efficient predictive maintenance in heavy-duty trucks.” Proceedings of the 22nd International Symposium on Intelligent Data Analysis (IDA), doi: 10.1007/978-3-031-58553-1_21. paper code

2023

Louis Carpentier, Jorik Jooken, Jan Goedgebeur. “A heuristic algorithm for the maximum happy vertices problem using tree decompositions.” Journal Of Heuristics, doi: 10.1007/s10732-023-09522-x. paper code

2022

Louis Carpentier, Jorik Jooken, Jan Goedgebeur. “A heuristic algorithm for the maximum happy vertices problem using tree decompositions.” arXiv: 2208.14921. preprint code