| 2025 | ACL | Mitigating Negative Interference in Multilingual Knowledge Editing through Null-Space Constraints. | Wei Sun, Tingyu Qu, Mingxiao Li, Jesse Davis, Marie-Francine Moens |
| 2025 | AISTATS | Learning from biased positive-unlabeled data via threshold calibration. | Pawel Teisseyre, Timo Martens, Jessa Bekker, Jesse Davis |
| 2025 | DSAA | Anomaly Detection Under Contaminated Data: A Weighted Iterative Refinement Framework for Health Monitoring. | Stefano Donn, Jesse Davis, Filip Van Utterbeeck, Mathias Verbeke |
| 2025 | ECAI | Policy Safety Testing in Non-Deterministic Planning: Fuzzing, Test Oracles, Fault Analysis. | Chaahat Jain, Daniel Sherbakov, Marcel Vinzent, Marcel Steinmetz, Jesse Davis, Jrg Hoffmann |
| 2025 | ICML | Compressing tree ensembles through Level-wise Optimization and Pruning. | Laurens Devos, Timo Martens, Deniz Can Oruc, Wannes Meert, Hendrik Blockeel, Jesse Davis |
| 2025 | IDA | The When and How of Target Variable Transformations. | Loren Nuyts, Jesse Davis |
| 2025 | KDD | RegCheck: A Real-Time Approach for Flagging Potentially Malicious Domain Name Registrations. | Thomas Daniels, Maarten Bosteels, Pieter Robberechts, Jesse Davis |
| 2024 | AAAI | Robustness Verification of Multi-Class Tree Ensembles. | Laurens Devos, Lorenzo Cascioli, Jesse Davis |
| 2024 | COLING | DMON: A Simple Yet Effective Approach for Argument Structure Learning. | Wei Sun, Mingxiao Li, Jingyuan Sun, Jesse Davis, Marie-Francine Moens |
| 2024 | ECAI | Safety Verification of Tree-Ensemble Policies via Predicate Abstraction. | Chaahat Jain, Lorenzo Cascioli, Laurens Devos, Marcel Vinzent, Marcel Steinmetz, Jesse Davis, Jrg Hoffmann |
| 2024 | ECAI | Combining Active Learning and Learning to Reject for Anomaly Detection. | Luca Stradiotti, Lorenzo Perini, Jesse Davis |
| 2024 | SDM | Semi-Supervised Isolation Forest for Anomaly Detection. | Luca Stradiotti, Lorenzo Perini, Jesse Davis |
| 2023 | KDD | Learning from Positive and Unlabeled Multi-Instance Bags in Anomaly Detection. | Lorenzo Perini, Vincent Vercruyssen, Jesse Davis |
| 2023 | KDD | un-xPass: Measuring Soccer Player's Creativity. | Pieter Robberechts, Maaike Van Roy, Jesse Davis |
| 2023 | SDM | A novel reject option applied to sleep stage scoring. | Dries Van der Plas, Wannes Meert, Johan Verbraecken, Jesse Davis |
| 2022 | AAAI | Transferring the Contamination Factor between Anomaly Detection Domains by Shape Similarity. | Lorenzo Perini, Vincent Vercruyssen, Jesse Davis |
| 2022 | AAAI | Unifying Knowledge Base Completion with PU Learning to Mitigate the Observation Bias. | Jonas Schouterden, Jessa Bekker, Jesse Davis, Hendrik Blockeel |
| 2022 | DIS | Semi-supervised Change Point Detection Using Active Learning. | Arne De Brabandere, Zhenxiang Cao, Maarten De Vos, Alexander Bertrand, Jesse Davis |
| 2022 | DIS | Elastic Product Quantization for Time Series. | Pieter Robberechts, Wannes Meert, Jesse Davis |
| 2022 | IJCAI | Evaluating Sports Analytics Models: Challenges, Approaches, and Lessons Learned. | Jesse Davis, Lotte Bransen, Laurens Devos, Wannes Meert, Pieter Robberechts, Jan Van Haaren, Maaike Van Roy |
| 2021 | ADMA | Know Your Limits: Machine Learning with Rejection for Vehicle Engineering. | Kilian Hendrickx, Wannes Meert, Bram Cornelis, Jesse Davis |
| 2021 | EMNLP | Mapping probability word problems to executable representations. | Simon Suster, Pieter Fivez, Pietro Totis, Angelika Kimmig, Jesse Davis, Luc De Raedt, Walter Daelemans |
| 2021 | ICML | Versatile Verification of Tree Ensembles. | Laurens Devos, Wannes Meert, Jesse Davis |
| 2021 | KDD | A Bayesian Approach to In-Game Win Probability in Soccer. | Pieter Robberechts, Jan Van Haaren, Jesse Davis |
| 2021 | SDM | Verifying Tree Ensembles by Reasoning about Potential Instances. | Laurens Devos, Wannes Meert, Jesse Davis |
| 2020 | AAAI | Transfer Learning for Anomaly Detection through Localized and Unsupervised Instance Selection. | Vincent Vercruyssen, Wannes Meert, Jesse Davis |
| 2020 | DIS | Multi-directional Rule Set Learning. | Jonas Schouterden, Jesse Davis, Hendrik Blockeel |
| 2020 | ECAI | STRiKE: Rule-Driven Relational Learning Using Stratified k-Entailment. | Martin Svatos, Steven Schockaert, Jesse Davis, Ondrej Kuzelka |
| 2020 | IJCAI | VAEP: An Objective Approach to Valuing On-the-Ball Actions in Soccer (Extended Abstract). | Tom Decroos, Lotte Bransen, Jan Van Haaren, Jesse Davis |
| 2020 | IJCAI | Class Prior Estimation in Active Positive and Unlabeled Learning. | Lorenzo Perini, Vincent Vercruyssen, Jesse Davis |
| 2020 | SDM | "Now you see it, now you don't!" Detecting Suspicious Pattern Absences in Continuous Time Series. | Vincent Vercruyssen, Wannes Meert, Jesse Davis |
| 2019 | DIS | Fast Distance-Based Anomaly Detection in Images Using an Inception-Like Autoencoder. | Natasa Sarafijanovic-Djukic, Jesse Davis |
| 2019 | ILP | LazyBum: Decision Tree Learning Using Lazy Propositionalization. | Jonas Schouterden, Jesse Davis, Hendrik Blockeel |
| 2019 | KDD | Actions Speak Louder than Goals: Valuing Player Actions in Soccer. | Tom Decroos, Lotte Bransen, Jan Van Haaren, Jesse Davis |
| 2019 | UAI | Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption. | Ondrej Kuzelka, Jesse Davis |
| 2018 | AAAI | Estimating the Class Prior in Positive and Unlabeled Data Through Decision Tree Induction. | Jessa Bekker, Jesse Davis |
| 2018 | AAAI | Relational Marginal Problems: Theory and Estimation. | Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert |
| 2018 | ICDM | Semi-Supervised Anomaly Detection with an Application to Water Analytics. | Vincent Vercruyssen, Wannes Meert, Gust Verbruggen, Koen Maes, Ruben Baumer, Jesse Davis |
| 2018 | KDD | Fatigue Prediction in Outdoor Runners Via Machine Learning and Sensor Fusion. | Tim Op De Beck, Wannes Meert, Kurt Schtte, Benedicte Vanwanseele, Jesse Davis |
| 2018 | KDD | Automatic Discovery of Tactics in Spatio-Temporal Soccer Match Data. | Tom Decroos, Jan Van Haaren, Jesse Davis |
| 2018 | WWW | Estimating Rule Quality for Knowledge Base Completion with the Relationship between Coverage Assumption. | Kaja Zupanc, Jesse Davis |
| 2018 | UAI | PAC-Reasoning in Relational Domains. | Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert |
| 2017 | AAAI | Predicting Soccer Highlights from Spatio-Temporal Match Event Streams. | Tom Decroos, Vladimir Dzyuba, Jan Van Haaren, Jesse Davis |
| 2017 | IJCAI | Solving Probability Problems in Natural Language. | Anton Dries, Angelika Kimmig, Jesse Davis, Vaishak Belle, Luc De Raedt |
| 2017 | IJCAI | Induction of Interpretable Possibilistic Logic Theories from Relational Data. | Ondrej Kuzelka, Jesse Davis, Steven Schockaert |
| 2017 | ILP | Positive and Unlabeled Relational Classification Through Label Frequency Estimation. | Jessa Bekker, Jesse Davis |
| 2016 | ECAI | Interpretable Encoding of Densities Using Possibilistic Logic. | Ondrej Kuzelka, Jesse Davis, Steven Schockaert |
| 2016 | ECAI | Learning the Structure of Dynamic Hybrid Relational Models. | Davide Nitti, Irma Ravkic, Jesse Davis, Luc De Raedt |
| 2016 | FIE | Student perspectives on application of game-based learning within a graduate-level engineering course. | Cheryl A. Bodnar, Renee M. Clark, Jesse Davis, Tom Congedo, Daniel Cole |
| 2016 | IJCAI | Learning Possibilistic Logic Theories from Default Rules. | Ondrej Kuzelka, Jesse Davis, Steven Schockaert |
| 2016 | IJCAI | Dynamic Early Stopping for Naive Bayes. | Aron Verachtert, Hendrik Blockeel, Jesse Davis |
| 2016 | KDD | Analyzing Volleyball Match Data from the 2014 World Championships Using Machine Learning Techniques. | Jan Van Haaren, Horesh Ben Shitrit, Jesse Davis, Pascal Fua |
| 2015 | AAAI | TODTLER: Two-Order-Deep Transfer Learning. | Jan Van Haaren, Andrey Kolobov, Jesse Davis |
| 2015 | AIME | Mining Hierarchical Pathology Data Using Inductive Logic Programming. | Tim Op De Beck, Arjen Hommersom, Jan Van Haaren, Maarten van der Heijden, Jesse Davis, Peter J. F. Lucas, Lucy Overbeek, Iris Nagtegaal |
| 2015 | IJCAI | Unsupervised Learning of an IS-A Taxonomy from a Limited Domain-Specific Corpus. | Daniele Alfarone, Jesse Davis |
| 2015 | ILP | Constructing Markov Logic Networks from First-Order Default Rules. | Ondrej Kuzelka, Jesse Davis, Steven Schockaert |
| 2015 | IDA | Automatically Discovering Offensive Patterns in Soccer Match Data. | Jan Van Haaren, Vladimir Dzyuba, Siebe Hannosset, Jesse Davis |
| 2015 | UAI | Encoding Markov logic networks in Possibilistic Logic. | Ondrej Kuzelka, Jesse Davis, Steven Schockaert |
| 2014 | CIKM | Repairing Inconsistent Taxonomies Using MAP Inference and Rules of Thumb. | Elie Merhej, Steven Schockaert, Martine De Cock, Marjon Blondeel, Daniele Alfarone, Jesse Davis |
| 2013 | AAAI | Lifted Generative Parameter Learning. | Guy Van den Broeck, Wannes Meert, Jesse Davis |
| 2013 | AAAI | On the Completeness of Lifted Variable Elimination. | Nima Taghipour, Daan Fierens, Guy Van den Broeck, Jesse Davis, Hendrik Blockeel |
| 2013 | AISTATS | Completeness Results for Lifted Variable Elimination. | Nima Taghipour, Daan Fierens, Guy Van den Broeck, Jesse Davis, Hendrik Blockeel |
| 2013 | ECSQARU | MCMC Estimation of Conditional Probabilities in Probabilistic Programming Languages. | Bogdan Moldovan, Ingo Thon, Jesse Davis, Luc De Raedt |
| 2013 | ILP | Generalized Counting for Lifted Variable Elimination. | Nima Taghipour, Jesse Davis, Hendrik Blockeel |
| 2012 | AAAI | Conditioning in First-Order Knowledge Compilation and Lifted Probabilistic Inference. | Guy Van den Broeck, Jesse Davis |
| 2012 | AAAI | Markov Network Structure Learning: A Randomized Feature Generation Approach. | Jan Van Haaren, Jesse Davis |
| 2012 | ICML | Unachievable Region in Precision-Recall Space and Its Effect on Empirical Evaluation. | Kendrick Boyd, Jesse Davis, David Page, Vtor Santos Costa |
| 2012 | ICML | Demand-Driven Clustering in Relational Domains for Predicting Adverse Drug Events. | Jesse Davis, Vtor Santos Costa, Elizabeth Berg, David Page, Peggy L. Peissig, Michael Caldwell |
| 2012 | ILP | Pairwise Markov Logic. | Daan Fierens, Kristian Kersting, Jesse Davis, Jian Chen, Martin Mladenov |
| 2012 | ILP | Hybrid Logical Bayesian Networks. | Irma Ravkic, Jan Ramon, Jesse Davis |
| 2011 | IJCAI | Lifted Probabilistic Inference by First-Order Knowledge Compilation. | Guy Van den Broeck, Nima Taghipour, Wannes Meert, Jesse Davis, Luc De Raedt |
| 2010 | EMNLP | Learning First-Order Horn Clauses from Web Text. | Stefan Schoenmackers, Jesse Davis, Oren Etzioni, Daniel S. Weld |
| 2010 | ICDM | Learning Markov Network Structure with Decision Trees. | Daniel Lowd, Jesse Davis |
| 2010 | ICML | Bottom-Up Learning of Markov Network Structure. | Jesse Davis, Pedro M. Domingos |
| 2009 | ICML | Deep transfer via second-order Markov logic. | Jesse Davis, Pedro M. Domingos |
| 2007 | ICML | An integrated approach to feature invention and model construction for drug activity prediction. | Jesse Davis, Vtor Santos Costa, Soumya Ray, David Page |
| 2007 | IJCAI | Change of Representation for Statistical Relational Learning. | Jesse Davis, Irene M. Ong, Jan Struyf, Elizabeth S. Burnside, David Page, Vtor Santos Costa |
| 2006 | ICML | The relationship between Precision-Recall and ROC curves. | Jesse Davis, Mark H. Goadrich |
| 2005 | AMIA | Knowledge Discovery from Structured Mammography Reports Using Inductive Logic Programming. | Elizabeth S. Burnside, Jesse Davis, Vtor Santos Costa, Ins de Castro Dutra, Charles E. Kahn Jr., Jason Fine, David Page |
| 2005 | IJCAI | View Learning for Statistical Relational Learning: With an Application to Mammography. | Jesse Davis, Elizabeth S. Burnside, Ins de Castro Dutra, David Page, Raghu Ramakrishnan, Vtor Santos Costa, Jude W. Shavlik |