Qualitative Spatial Reasoning for Soccer Pass Prediction. - Vincent Vercruyssen; Luc De Raedt; Jesse Davis (MLSA@PKDD/ECML, 2016)

Transfer Learning for Time Series Anomaly Detection. - Vincent Vercruyssen; Wannes Meert; Jesse Davis (IAL@PKDD/ECML, 2017)

Semi-Supervised Anomaly Detection with an Application to Water Analytics. - Vincent Vercruyssen; Wannes Meert; Gust Verbruggen; Koen Maes; Ruben Baumer; Jesse Davis (ICDM, 2018)

Pattern-Based Anomaly Detection in Mixed-Type Time Series. - Len Feremans; Vincent Vercruyssen; Boris Cule; Wannes Meert; Bart Goethals (ECML/PKDD (1), 2019)

A Framework for Pattern Mining and Anomaly Detection in Multi-dimensional Time Series and Event Logs. - Len Feremans; Vincent Vercruyssen; Wannes Meert; Boris Cule; Bart Goethals (NFMCP@PKDD/ECML, 2019)

Transfer Learning for Anomaly Detection through Localized and Unsupervised Instance Selection. - Vincent Vercruyssen; Wannes Meert; Jesse Davis (AAAI, 2020)

Class Prior Estimation in Active Positive and Unlabeled Learning. - Lorenzo Perini; Vincent Vercruyssen; Jesse Davis (IJCAI, 2020)

A Ranking Stability Measure for Quantifying the Robustness of Anomaly Detection Methods. - Lorenzo Perini; Connor Galvin; Vincent Vercruyssen (PKDD/ECML Workshops, 2020)

Quantifying the Confidence of Anomaly Detectors in Their Example-Wise Predictions. - Lorenzo Perini; Vincent Vercruyssen; Jesse Davis (ECML/PKDD (3), 2020)

"Now you see it, now you don't!" Detecting Suspicious Pattern Absences in Continuous Time Series. - Vincent Vercruyssen; Wannes Meert; Jesse Davis (SDM, 2020)

Why Are You Weird? Infusing Interpretability in Isolation Forest for Anomaly Detection. - Nirmal Sobha Kartha; Clément Gautrais; Vincent Vercruyssen (CoRR, 2021)

Transferring the Contamination Factor between Anomaly Detection Domains by Shape Similarity. - Lorenzo Perini; Vincent Vercruyssen; Jesse Davis (AAAI, 2022)

Systematic Evaluation of CASH Search Strategies for Unsupervised Anomaly Detection. - Ioannis Antoniadis 001; Vincent Vercruyssen; Jesse Davis (LIDTA, 2022)

Multi-domain Active Learning for Semi-supervised Anomaly Detection. - Vincent Vercruyssen; Lorenzo Perini; Wannes Meert; Jesse Davis (ECML/PKDD (4), 2022)

Learning from Positive and Unlabeled Multi-Instance Bags in Anomaly Detection. - Lorenzo Perini; Vincent Vercruyssen; Jesse Davis (KDD, 2023)

AD-MERCS: Modeling Normality and Abnormality in Unsupervised Anomaly Detection. - Jonas Soenen; Elia Van Wolputte; Vincent Vercruyssen; Wannes Meert; Hendrik Blockeel (CoRR, 2023)