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Researcher
Vincent Vercruyssen
- Disciplines:Artificial intelligence
Affiliations
- Declarative Languages and Artificial Intelligence (DTAI) (Division)
Member
From1 Aug 2020 → Today - Informatics Section (Division)
Member
From15 Sep 2015 → 4 Aug 2020
Projects
1 - 2 of 2
- Anomaly Detection in Massive Time SeriesFrom1 Jan 2021 → 31 Dec 2022Funding: IWT / VLAIO personal funding - innovation mandates
- Designing Anomaly Detection Algorithms that Exploit Flexible SupervisionFrom28 Sep 2015 → 18 Dec 2020Funding: Own budget, for example: patrimony, inscription fees, gifts
Publications
1 - 10 of 12
- Learning from Positive and Unlabeled Multi-Instance Bags in Anomaly Detection(2023)
Authors: Lorenzo Perini, Vincent Vercruyssen, Jesse Davis
Pages: 1897 - 1906Number of pages: 10 - Why Are You Weird? Infusing Interpretability in Isolation Forest for Anomaly Detection(2021)
Authors: Vincent Vercruyssen
Pages: 51 - 57Number of pages: 7 - A Ranking Stability Measure for Quantifying the Robustness of Anomaly Detection Methods(2021)
Authors: Lorenzo Perini, Vincent Vercruyssen
Pages: 397 - 408 - Quantifying the Confidence of Anomaly Detectors in Their Example-Wise Predictions(2021)
Authors: Lorenzo Perini, Vincent Vercruyssen, Jesse Davis
Pages: 227 - 243Number of pages: 17 - Designing Anomaly Detection Algorithms that Exploit Flexible Supervision(2020)
Authors: Vincent Vercruyssen, Jesse Davis, Wannes Meert
- Transfer Learning for Anomaly Detection through Localized and Unsupervised Instance Selection(2020)
Authors: Vincent Vercruyssen, Wannes Meert, Jesse Davis
Pages: 6054 - 6061 - "Now you see it, now you don't!" Detecting Suspicious Pattern Absences in Continuous Time Series(2020)
Authors: Vincent Vercruyssen, Wannes Meert, Jesse Davis
Pages: 127 - 135Number of pages: 9 - Pattern-Based Anomaly Detection in Mixed-Type Time Series(2020)
Authors: Vincent Vercruyssen, Wannes Meert
Pages: 240 - 256Number of pages: 16 - A Framework for Pattern Mining and Anomaly Detection in Multi-Dimensional Time Series and Event Logs(2019)
Authors: Vincent Vercruyssen, Wannes Meert
Pages: 3 - 20Number of pages: 17 - Semi-supervised Anomaly Detection with an Application to Water Analytics(2018)
Authors: Vincent Vercruyssen, Wannes Meert, Gust Verbruggen, Jesse Davis
Pages: 527 - 536Number of pages: 10