Evolving Vision-Based Flying Robots. - Jean-Christophe Zufferey; Dario Floreano; Matthijs van Leeuwen; Tancredi Merenda (Biologically Motivated Computer Vision, 2002)

Compression Picks Item Sets That Matter. - Matthijs van Leeuwen; Jilles Vreeken; Arno Siebes (PKDD, 2006)

Item Sets that Compress. - Arno Siebes; Jilles Vreeken; Matthijs van Leeuwen (SDM, 2006)

Preserving Privacy through Data Generation. - Jilles Vreeken; Matthijs van Leeuwen; Arno Siebes (ICDM, 2007)

Characterising the difference. - Jilles Vreeken; Matthijs van Leeuwen; Arno Siebes (KDD, 2007)

StreamKrimp: Detecting Change in Data Streams. - Matthijs van Leeuwen; Arno Siebes (ECML/PKDD (1), 2008)

Compressing tags to find interesting media groups. - Matthijs van Leeuwen; Francesco Bonchi; Börkur Sigurbjörnsson; Arno Siebes (CIKM, 2009)

Identifying the components. - Matthijs van Leeuwen; Jilles Vreeken; Arno Siebes (Data Min. Knowl. Discov., 2009)

Subgroup Discovery Meets Bayesian Networks – An Exceptional Model Mining Approach. - Wouter Duivesteijn; Arno J. Knobbe; Ad Feelders; Matthijs van Leeuwen (ICDM, 2010)

Maximal exceptions with minimal descriptions. - Matthijs van Leeuwen (Data Min. Knowl. Discov., 2010)

Patterns that matter. - Matthijs van Leeuwen (2010)

Non-redundant Subgroup Discovery in Large and Complex Data. - Matthijs van Leeuwen; Arno J. Knobbe (ECML/PKDD (3), 2011)

Characterizing Uncertain Data using Compression. - Francesco Bonchi; Matthijs van Leeuwen; Antti Ukkonen (SDM, 2011)

Krimp: mining itemsets that compress. - Jilles Vreeken; Matthijs van Leeuwen; Arno Siebes (Data Min. Knowl. Discov., 2011)

Mining Local Staircase Patterns in Noisy Data. - Thanh Le Van; Ana Carolina Fierro; Tias Guns; Matthijs van Leeuwen; Siegfried Nijssen; Luc De Raedt; Kathleen Marchal (ICDM Workshops, 2012)

Improving Tag Recommendation Using Few Associations. - Matthijs van Leeuwen; Diyah Puspitaningrum (IDA, 2012)

Diverse subgroup set discovery. - Matthijs van Leeuwen; Arno J. Knobbe (Data Min. Knowl. Discov., 2012)

Active Preference Learning for Ranking Patterns. - Vladimir Dzyuba; Matthijs van Leeuwen; Siegfried Nijssen; Luc De Raedt (ICTAI, 2013)

Interactive Discovery of Interesting Subgroup Sets. - Vladimir Dzyuba; Matthijs van Leeuwen (IDA, 2013)

Discovering Skylines of Subgroup Sets. - Matthijs van Leeuwen; Antti Ukkonen (ECML/PKDD (3), 2013)

Mining and Using Sets of Patterns through Compression. - Matthijs van Leeuwen; Jilles Vreeken (Frequent Pattern Mining, 2014)

Fast Estimation of the Pattern Frequency Spectrum. - Matthijs van Leeuwen; Antti Ukkonen (ECML/PKDD (2), 2014)

Ranked Tiling. - Thanh Le Van; Matthijs van Leeuwen; Siegfried Nijssen; Ana Carolina Fierro; Kathleen Marchal; Luc De Raedt (ECML/PKDD (2), 2014)

Estimating the pattern frequency spectrum inside the browser. - Matthijs van Leeuwen; Antti Ukkonen (CoRR, 2014)

Interactive Learning of Pattern Rankings. - Vladimir Dzyuba; Matthijs van Leeuwen; Siegfried Nijssen; Luc De Raedt (Int. J. Artif. Intell. Tools, 2014)

Description-Driven Community Detection. - Simon Pool; Francesco Bonchi; Matthijs van Leeuwen (ACM Trans. Intell. Syst. Technol., 2014)

Interactive Data Exploration Using Pattern Mining. - Matthijs van Leeuwen (Interactive Knowledge Discovery and Data Mining in Biomedical Informatics, 2014)

Finding Subspace Clusters Using Ranked Neighborhoods. - Emin Aksehirli; Siegfried Nijssen; Matthijs van Leeuwen; Bart Goethals (ICDM Workshops, 2015)

An Exercise in Declarative Modeling for Relational Query Mining. - Sergey Paramonov 001; Matthijs van Leeuwen; Marc Denecker; Luc De Raedt (ILP, 2015)

Rank Matrix Factorisation. - Thanh Le Van; Matthijs van Leeuwen; Siegfried Nijssen; Luc De Raedt (PAKDD (1), 2015)

VIPER - Visual Pattern Explorer. - Matthijs van Leeuwen; Lara Cardinaels (ECML/PKDD (3), 2015)

Same bang, fewer bucks: efficient discovery of the cost-influence skyline. - Matthijs van Leeuwen; Antti Ukkonen (SDM, 2015)

Association Discovery in Two-View Data. - Matthijs van Leeuwen; Esther Galbrun (IEEE Trans. Knowl. Data Eng., 2015)

Local subspace-based outlier detection using global neighbourhoods. - Bas van Stein; Matthijs van Leeuwen; Thomas Bäck (IEEE BigData, 2016)

Expect the Unexpected - On the Significance of Subgroups. - Matthijs van Leeuwen; Antti Ukkonen (DS, 2016)

Evolving the structure of Evolution Strategies. - Sander van Rijn; Hao Wang 025; Matthijs van Leeuwen; Thomas Bäck (SSCI, 2016)

Simultaneous discovery of cancer subtypes and subtype features by molecular data integration. - Thanh Le Van; Matthijs van Leeuwen; Ana Carolina Fierro; Dries De Maeyer; Jimmy Van den Eynden; Lieven P. C. Verbeke; Luc De Raedt; Kathleen Marchal; Siegfried Nijssen (Bioinform., 2016)

Subjective interestingness of subgraph patterns. - Matthijs van Leeuwen; Tijl De Bie; Eirini Spyropoulou; Cédric Mesnage (Mach. Learn., 2016)

Learning What Matters - Sampling Interesting Patterns. - Vladimir Dzyuba; Matthijs van Leeuwen (PAKDD (1), 2017)

Explaining Deviating Subsets Through Explanation Networks. - Antti Ukkonen; Vladimir Dzyuba; Matthijs van Leeuwen (ECML/PKDD (2), 2017)

Flexible constrained sampling with guarantees for pattern mining. - Vladimir Dzyuba; Matthijs van Leeuwen; Luc De Raedt (Data Min. Knowl. Discov., 2017)

Relational data factorization. - Sergey Paramonov 001; Matthijs van Leeuwen; Luc De Raedt (Mach. Learn., 2017)

Semiring Rank Matrix Factorization. - Thanh Le Van; Siegfried Nijssen; Matthijs van Leeuwen; Luc De Raedt (IEEE Trans. Knowl. Data Eng., 2017)

Multi-fidelity surrogate model approach to optimization. - Sander van Rijn; Sebastian Schmitt; Markus Olhofer; Matthijs van Leeuwen; Thomas Bäck (GECCO (Companion), 2018)

Identifying flight delay patterns using diverse subgroup discovery. - Hugo Manuel Proença; Ruben Klijn; Thomas Bäck; Matthijs van Leeuwen (SSCI, 2018)

Challenges and Limitations in Clustering Blood Donor Hemoglobin Trajectories. - Marieke Vinkenoog; Mart P. Janssen; Matthijs van Leeuwen (AALTD@PKDD/ECML, 2019)

Addendum to the Special Issue on Interactive Data Exploration and Analytics (TKDD, Vol. 12 Iss. 1). - Matthijs van Leeuwen; Polo Chau; Jilles Vreeken; Dafna Shahaf; Christos Faloutsos (ACM Trans. Knowl. Discov. Data, 2019)

Vouw: Geometric Pattern Mining Using the MDL Principle. - Micky Faas; Matthijs van Leeuwen (IDA, 2020)

Widening for MDL-Based Retail Signature Discovery. - Clément Gautrais; Peggy Cellier; Matthijs van Leeuwen; Alexandre Termier (IDA, 2020)

Discovering Outstanding Subgroup Lists for Numeric Targets Using MDL. - Hugo Manuel Proença; Peter Grünwald; Thomas Bäck; Matthijs van Leeuwen (ECML/PKDD (1), 2020)

Interpretable multiclass classification by MDL-based rule lists. - Hugo Manuel Proença; Matthijs van Leeuwen (Inf. Sci., 2020)

Discovering subjectively interesting multigraph patterns. - Sarang Kapoor; Dhish Kumar Saxena; Matthijs van Leeuwen (Mach. Learn., 2020)

Estimating Conditional Mutual Information for Discrete-Continuous Mixtures using Multi-Dimensional Adaptive Histograms. - Alexander Marx 001; Lincen Yang; Matthijs van Leeuwen (SDM, 2021)

Finding Efficient Trade-offs in Multi-Fidelity Response Surface Modeling. - Sander van Rijn; Sebastian Schmitt; Matthijs van Leeuwen; Thomas Bäck (CoRR, 2021)

Robust subgroup discovery. - Hugo Manuel Proença; Thomas Bäck; Matthijs van Leeuwen (CoRR, 2021)

Online summarization of dynamic graphs using subjective interestingness for sequential data. - Sarang Kapoor; Dhish Kumar Saxena; Matthijs van Leeuwen (Data Min. Knowl. Discov., 2021)

Finding Efficient Trade-offs in Multi-Fidelity Response Surface Modeling: Generated data files and figures. - Sander van Rijn; Sebastian Schmitt; Matthijs van Leeuwen; Thomas Bäck (Zenodo, 2021)

Histogram-based Probabilistic Rule Lists for Numeric Targets (short paper). - Lincen Yang; Tim Opdam; Matthijs van Leeuwen (KDID, 2022)

Truly Unordered Probabilistic Rule Sets for Multi-class Classification. - Lincen Yang; Matthijs van Leeuwen (ECML/PKDD (5), 2022)

Robust subgroup discovery. - Hugo Manuel Proença; Peter Grünwald; Thomas Bäck; Matthijs van Leeuwen (Data Min. Knowl. Discov., 2022)

Generating synthetic mixed discrete-continuous health records with mixed sum-product networks. - Shannon K. S. Kroes; Matthijs van Leeuwen; Rolf H. H. Groenwold; Mart P. Janssen (J. Am. Medical Informatics Assoc., 2022)

Feature Selection for Fault Detection and Prediction based on Event Log Analysis. - Zhong Li 002; Matthijs van Leeuwen (SIGKDD Explor., 2022)

Finding Efficient Trade-offs in Multi-Fidelity Response Surface Modeling: Generated data files and figures. - Sander van Rijn; Sebastian Schmitt; Matthijs van Leeuwen; Thomas Bäck (Zenodo, 2022)

Novel Approach for Phenotyping Based on Diverse Top-K Subgroup Lists. - Antonio Lopez-Martinez-Carrasco; Hugo Manuel Proença; Jose M. Juarez; Matthijs van Leeuwen; Manuel Campos (AIME, 2023)

Discovering Diverse Top-K Characteristic Lists. - Antonio Lopez-Martinez-Carrasco; Hugo Manuel Proença; Jose M. Juarez; Matthijs van Leeuwen; Manuel Campos (IDA, 2023)

Discovering Rule Lists with Preferred Variables. - Ioanna Papagianni; Matthijs van Leeuwen (IDA, 2023)

Robust and Explainable Contextual Anomaly Detection using Quantile Regression Forests. - Zhong Li 002; Matthijs van Leeuwen (CoRR, 2023)

WEARDA: recording wearable sensor data for human activity monitoring. - Richard van Dijk; Daniela Gawehns; Matthijs van Leeuwen (CoRR, 2023)

Graph Neural Network based Log Anomaly Detection and Explanation. - Zhong Li 002; Jiayang Shi; Matthijs van Leeuwen (CoRR, 2023)

Unsupervised discretization by two-dimensional MDL-based histogram. - Lincen Yang; Mitra Baratchi; Matthijs van Leeuwen (Mach. Learn., 2023)

Explainable contextual anomaly detection using quantile regression forests. - Zhong Li 002; Matthijs van Leeuwen (Data Min. Knowl. Discov., 2023)

Evaluating Cluster-Based Synthetic Data Generation for Blood-Transfusion Analysis. - Shannon K. S. Kroes; Matthijs van Leeuwen; Rolf H. H. Groenwold; Mart P. Janssen (J. Cybersecur. Priv., 2023)

Graph Neural Networks based Log Anomaly Detection and Explanation. - Zhong Li 002; Jiayang Shi; Matthijs van Leeuwen (ICSE Companion, 2024)

Conditional Density Estimation with Histogram Trees. - Lincen Yang; Matthijs van Leeuwen (NeurIPS, 2024)

Probabilistic Truly Unordered Rule Sets. - Lincen Yang; Matthijs van Leeuwen (CoRR, 2024)

Explainable Graph Neural Networks Under Fire. - Zhong Li 002; Simon Geisler; Yuhang Wang; Stephan Günnemann; Matthijs van Leeuwen (CoRR, 2024)

Directional anomaly detection. - Oliver Urs Lenz; Matthijs van Leeuwen (CoRR, 2024)

A Survey on Explainable Anomaly Detection. - Zhong Li 002; Yuxuan Zhu; Matthijs van Leeuwen (ACM Trans. Knowl. Discov. Data, 2024)

Cross-Domain Graph Level Anomaly Detection. - Zhong Li 002; Sheng Liang; Jiayang Shi; Matthijs van Leeuwen (IEEE Trans. Knowl. Data Eng., 2024)

Discovering multiple antibiotic resistance phenotypes using diverse top-k subgroup list discovery. - Antonio Lopez-Martinez-Carrasco; Hugo Manuel Proença; Jose M. Juarez; Matthijs van Leeuwen; Manuel Campos (Artif. Intell. Medicine, 2025)

Diffusion Models for Tabular Data: Challenges, Current Progress, and Future Directions. - Zhong Li 002; Qi Huang; Lincen Yang; Jiayang Shi; Zhao Yang; Niki van Stein; Thomas Bäck; Matthijs van Leeuwen (CoRR, 2025)

Towards automated self-supervised learning for truly unsupervised graph anomaly detection. - Zhong Li 002; Yuhang Wang; Matthijs van Leeuwen (Data Min. Knowl. Discov., 2025)