Friendly Object Tracking and Foreign Object Detection and Localization with an SDAC Wireless Sensor Network. - Douglas Stark; Jesse Davis (FTDCS, 2004)

Knowledge Discovery from Structured Mammography Reports Using Inductive Logic Programming. - Elizabeth S. Burnside; Jesse Davis; Vítor Santos Costa; Inês de Castro Dutra; Charles E. Kahn Jr.; Jason Fine; David Page (AMIA, 2005)

An Integrated Approach to Learning Bayesian Networks of Rules. - Jesse Davis; Elizabeth S. Burnside; Inês de Castro Dutra; David Page; Vítor Santos Costa (ECML, 2005)

View Learning for Statistical Relational Learning: With an Application to Mammography. - Jesse Davis; Elizabeth S. Burnside; Inês de Castro Dutra; David Page; Raghu Ramakrishnan 001; Vítor Santos Costa; Jude W. Shavlik (IJCAI, 2005)

Mass: modular architecture for sensor systems. - Nicholas Gerard Edmonds; Douglas Stark; Jesse Davis (IPSN, 2005)

Method Of Interaction In A Modular Architecture For Sensor Systems (Mass). - Jesse Davis; Douglas Stark; Nicholas Gerard Edmonds (Int. J. Softw. Eng. Knowl. Eng., 2005)

An Efficient Approximation to Lookahead in Relational Learners. - Jan Struyf; Jesse Davis; C. David Page Jr. (ECML, 2006)

The relationship between Precision-Recall and ROC curves. - Jesse Davis; Mark H. Goadrich (ICML, 2006)

An integrated approach to feature invention and model construction for drug activity prediction. - Jesse Davis; Vítor Santos Costa; Soumya Ray; David Page (ICML, 2007)

Change of Representation for Statistical Relational Learning. - Jesse Davis; Irene M. Ong; Jan Struyf; Elizabeth S. Burnside; David Page; Vítor Santos Costa (IJCAI, 2007)

Deep transfer via second-order Markov logic. - Jesse Davis; Pedro M. Domingos (ICML, 2009)

Learning First-Order Horn Clauses from Web Text. - Stefan Schoenmackers; Jesse Davis; Oren Etzioni; Daniel S. Weld (EMNLP, 2010)

Learning Markov Network Structure with Decision Trees. - Daniel Lowd; Jesse Davis (ICDM, 2010)

Bottom-Up Learning of Markov Network Structure. - Jesse Davis; Pedro M. Domingos (ICML, 2010)

Lifted Probabilistic Inference by First-Order Knowledge Compilation. - Guy Van den Broeck; Nima Taghipour; Wannes Meert; Jesse Davis; Luc De Raedt (IJCAI, 2011)

Deep Transfer: A Markov Logic Approach. - Jesse Davis; Pedro M. Domingos (AI Mag., 2011)

Conditioning in First-Order Knowledge Compilation and Lifted Probabilistic Inference. - Guy Van den Broeck; Jesse Davis (AAAI, 2012)

Markov Network Structure Learning: A Randomized Feature Generation Approach. - Jan Van Haaren; Jesse Davis (AAAI, 2012)

A Text Mining Approach as Baseline for QA4MRE'12. - Mathias Verbeke; Jesse Davis (CLEF (Online Working Notes/Labs/Workshop), 2012)

Unachievable Region in Precision-Recall Space and Its Effect on Empirical Evaluation. - Kendrick Boyd; Jesse Davis; David Page; Vítor Santos Costa (ICML, 2012)

Demand-Driven Clustering in Relational Domains for Predicting Adverse Drug Events. - Jesse Davis; Vítor Santos Costa; Elizabeth Berg; David Page; Peggy L. Peissig; Michael Caldwell (ICML, 2012)

Pairwise Markov Logic. - Daan Fierens; Kristian Kersting; Jesse Davis; Jian Chen; Martin Mladenov (ILP, 2012)

Hybrid Logical Bayesian Networks. - Irma Ravkic; Jan Ramon; Jesse Davis (ILP (Late Breaking Papers), 2012)

Generalized Counting for Lifted Variable Elimination. - Nima Taghipour; Jesse Davis (StarAI@UAI, 2012)

Lifted Variable Elimination: A Novel Operator and Completeness Results - Nima Taghipour; Daan Fierens; Guy Van den Broeck; Jesse Davis; Hendrik Blockeel (CoRR, 2012)

Lifted Variable Elimination with Arbitrary Constraints. - Nima Taghipour; Daan Fierens; Jesse Davis; Hendrik Blockeel (AISTATS, 2012)

Lifted Generative Parameter Learning. - Guy Van den Broeck; Wannes Meert; Jesse Davis (StarAI@AAAI, 2013)

On the Completeness of Lifted Variable Elimination. - Nima Taghipour; Daan Fierens; Guy Van den Broeck; Jesse Davis; Hendrik Blockeel (StarAI@AAAI, 2013)

Completeness Results for Lifted Variable Elimination. - Nima Taghipour; Daan Fierens; Guy Van den Broeck; Jesse Davis; Hendrik Blockeel (AISTATS, 2013)

MCMC Estimation of Conditional Probabilities in Probabilistic Programming Languages. - Bogdan Moldovan; Ingo Thon; Jesse Davis; Luc De Raedt (ECSQARU, 2013)

Generalized Counting for Lifted Variable Elimination. - Nima Taghipour; Jesse Davis; Hendrik Blockeel (ILP, 2013)

First-order Decomposition Trees. - Nima Taghipour; Jesse Davis; Hendrik Blockeel (NIPS, 2013)

Lifted Variable Elimination: Decoupling the Operators from the Constraint Language. - Nima Taghipour; Daan Fierens; Jesse Davis; Hendrik Blockeel (J. Artif. Intell. Res., 2013)

Repairing Inconsistent Taxonomies Using MAP Inference and Rules of Thumb. - Elie Merhej; Steven Schockaert; Martine De Cock; Marjon Blondeel; Daniele Alfarone; Jesse Davis (Web-KRM@CIKM, 2014)

Automatically Detecting and Rating Product Aspects from Textual Customer Reviews. - Wouter Bancken; Daniele Alfarone; Jesse Davis (DMNLP@PKDD/ECML, 2014)

Improving Markov network structure learning using decision trees. - Daniel Lowd; Jesse Davis (J. Mach. Learn. Res., 2014)

Predicting Adverse Drug Events from Electronic Medical Records. - Jesse Davis; Vítor Santos Costa; Peggy L. Peissig; Michael Caldwell; David Page (Foundations of Biomedical Knowledge Representation, 2015)

Treatment of Disease: The Role of Knowledge Representation for Treatment Selection. - Jesse Davis; Luis Enrique Sucar; Felipe Orihuela-Espina (Foundations of Biomedical Knowledge Representation, 2015)

TODTLER: Two-Order-Deep Transfer Learning. - Jan Van Haaren; Andrey Kolobov; Jesse Davis (AAAI, 2015)

Mining Hierarchical Pathology Data Using Inductive Logic Programming. - Tim Op De Beéck; Arjen Hommersom; Jan Van Haaren; Maarten van der Heijden; Jesse Davis; Peter J. F. Lucas; Lucy Overbeek; Iris Nagtegaal (AIME, 2015)

Automatically Discovering Offensive Patterns in Soccer Match Data. - Jan Van Haaren; Vladimir Dzyuba; Siebe Hannosset; Jesse Davis (IDA, 2015)

Unsupervised Learning of an IS-A Taxonomy from a Limited Domain-Specific Corpus. - Daniele Alfarone; Jesse Davis (IJCAI, 2015)

Constructing Markov Logic Networks from First-Order Default Rules. - Ondrej Kuzelka; Jesse Davis; Steven Schockaert (ILP, 2015)

Tractable Learning for Complex Probability Queries. - Jessa Bekker; Jesse Davis; Arthur Choi; Adnan Darwiche; Guy Van den Broeck (NIPS, 2015)

A Note on the Evaluation of Mutation Prioritization Algorithms. - Dusan Popovic; Jesse Davis; Alejandro Sifrim; Bart De Moor (SSCI, 2015)

Encoding Markov logic networks in Possibilistic Logic. - Ondrej Kuzelka; Jesse Davis; Steven Schockaert (UAI, 2015)

Problems with the nested granularity of feature domains in bioinformatics: the eXtasy case. - Dusan Popovic; Alejandro Sifrim; Jesse Davis; Yves Moreau; Bart De Moor (BMC Bioinform., 2015)

Assessing binary classifiers using only positive and unlabeled data. - Marc Claesen; Jesse Davis; Frank De Smet; Bart De Moor (CoRR, 2015)

Learning relational dependency networks in hybrid domains. - Irma Ravkic; Jan Ramon; Jesse Davis (Mach. Learn., 2015)

Topic modeling of biomedical text. - Sarah ElShal; Mithila Mathad; Jaak Simm; Jesse Davis; Yves Moreau (BIBM, 2016)

Interpretable Encoding of Densities Using Possibilistic Logic. - Ondrej Kuzelka; Jesse Davis; Steven Schockaert (ECAI, 2016)

Learning the Structure of Dynamic Hybrid Relational Models. - Davide Nitti 001; Irma Ravkic; Jesse Davis; Luc De Raedt (ECAI, 2016)

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 (FIE, 2016)

Learning Possibilistic Logic Theories from Default Rules. - Ondrej Kuzelka; Jesse Davis; Steven Schockaert (IJCAI, 2016)

Dynamic Early Stopping for Naive Bayes. - Aäron Verachtert; Hendrik Blockeel; Jesse Davis (IJCAI, 2016)

A Comprehensive Comparison of Two MEDLINE Annotators for Disease and Gene Linkage: Sometimes Less is More. - Sarah ElShal; Jaak Simm; Adam Arany; Pooya Zakeri; Jesse Davis; Yves Moreau (IWBBIO, 2016)

Analyzing Volleyball Match Data from the 2014 World Championships Using Machine Learning Techniques. - Jan Van Haaren; Horesh Ben Shitrit; Jesse Davis; Pascal Fua (KDD, 2016)

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

Measuring Adverse Drug Effects on Multimorbity using Tractable Bayesian Networks. - Jessa Bekker; Arjen Hommersom; Martijn Lappenschaar; Jesse Davis (CoRR, 2016)

Stratified Knowledge Bases as Interpretable Probabilistic Models (Extended Abstract). - Ondrej Kuzelka; Jesse Davis; Steven Schockaert (CoRR, 2016)

Guest editors introduction: special issue on inductive logic programming. - Jesse Davis; Jan Ramon (Mach. Learn., 2016)

Lifted generative learning of Markov logic networks. - Jan Van Haaren; Guy Van den Broeck; Wannes Meert; Jesse Davis (Mach. Learn., 2016)

Predicting Soccer Highlights from Spatio-Temporal Match Event Streams. - Tom Decroos; Vladimir Dzyuba; Jan Van Haaren; Jesse Davis (AAAI, 2017)

Solving Probability Problems in Natural Language. - Anton Dries; Angelika Kimmig; Jesse Davis; Vaishak Belle; Luc De Raedt (IJCAI, 2017)

Induction of Interpretable Possibilistic Logic Theories from Relational Data. - Ondrej Kuzelka; Jesse Davis; Steven Schockaert (IJCAI, 2017)

Positive and Unlabeled Relational Classification Through Label Frequency Estimation. - Jessa Bekker; Jesse Davis (ILP, 2017)

STARSS: A Spatio-Temporal Action Rating System for Soccer. - Tom Decroos; Jan Van Haaren; Vladimir Dzyuba; Jesse Davis (MLSA@PKDD/ECML, 2017)

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

Predicting the Potential of Professional Soccer Players. - Ruben Vroonen; Tom Decroos; Jan Van Haaren; Jesse Davis (MLSA@PKDD/ECML, 2017)

Estimating the Class Prior in Positive and Unlabeled Data Through Decision Tree Induction. - Jessa Bekker; Jesse Davis (AAAI, 2018)

Relational Marginal Problems: Theory and Estimation. - Ondrej Kuzelka; Yuyi Wang 001; Jesse Davis; Steven Schockaert (AAAI, 2018)

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

Fatigue Prediction in Outdoor Runners Via Machine Learning and Sensor Fusion. - Tim Op De Beéck; Wannes Meert; Kurt Schütte 002; Benedicte Vanwanseele; Jesse Davis (KDD, 2018)

Automatic Discovery of Tactics in Spatio-Temporal Soccer Match Data. - Tom Decroos; Jan Van Haaren; Jesse Davis (KDD, 2018)

Learning from Positive and Unlabeled Data under the Selected At Random Assumption. - Jessa Bekker; Jesse Davis (LIDTA@ECML/PKDD, 2018)

AMIE: Automatic Monitoring of Indoor Exercises. - Tom Decroos; Kurt Schütte 002; Tim Op De Beéck; Benedicte Vanwanseele; Jesse Davis (ECML/PKDD (3), 2018)

Query Log Analysis: Detecting Anomalies in DNS Traffic at a TLD Resolver. - Pieter Robberechts; Maarten Bosteels; Jesse Davis; Wannes Meert (DMLE/IOTSTREAMING@PKDD/ECML, 2018)

Forecasting the FIFA World Cup - Combining Result- and Goal-Based Team Ability Parameters. - Pieter Robberechts; Jesse Davis (MLSA@PKDD/ECML, 2018)

PAC-Reasoning in Relational Domains. - Ondrej Kuzelka; Yuyi Wang 001; Jesse Davis; Steven Schockaert (UAI, 2018)

Estimating Rule Quality for Knowledge Base Completion with the Relationship between Coverage Assumption. - Kaja Zupanc; Jesse Davis (WWW, 2018)

Beyond the Selected Completely At Random Assumption for Learning from Positive and Unlabeled Data. - Jessa Bekker; Jesse Davis (CoRR, 2018)

Introduction to the special issue for the ECML PKDD 2018 journal track. - Derek Greene; Björn Bringmann; Élisa Fromont; Jesse Davis (Data Min. Knowl. Discov., 2018)

Graph sampling with applications to estimating the number of pattern embeddings and the parameters of a statistical relational model. - Irma Ravkic; Martin Znidarsic; Jan Ramon; Jesse Davis (Data Min. Knowl. Discov., 2018)

Guest editors introduction to the special issue for the ECML PKDD 2018 journal track. - Jesse Davis; Björn Bringmann; Élisa Fromont; Derek Greene (Mach. Learn., 2018)

Fast Distance-Based Anomaly Detection in Images Using an Inception-Like Autoencoder. - Natasa Sarafijanovic-Djukic; Jesse Davis (DS, 2019)

Use of wearable technology to quantify fall risk in psychogeriatric environments: a feasability study. - Marc Mertens; Julie Raepsaet; Glen Debard; Mieke Mondelaers; Bart Vanrumste; Jesse Davis (EMBC, 2019)

LazyBum: Decision Tree Learning Using Lazy Propositionalization. - Jonas Schouterden; Jesse Davis; Hendrik Blockeel (ILP, 2019)

Actions Speak Louder than Goals: Valuing Player Actions in Soccer. - Tom Decroos; Lotte Bransen; Jan Van Haaren; Jesse Davis (KDD, 2019)

Beyond the Selected Completely at Random Assumption for Learning from Positive and Unlabeled Data. - Jessa Bekker; Pieter Robberechts; Jesse Davis (ECML/PKDD (2), 2019)

Player Vectors: Characterizing Soccer Players' Playing Style from Match Event Streams. - Tom Decroos; Jesse Davis (ECML/PKDD (3), 2019)

Fast Gradient Boosting Decision Trees with Bit-Level Data Structures. - Laurens Devos; Wannes Meert; Jesse Davis (ECML/PKDD (1), 2019)

Analyzing Soccer Players' Skill Ratings Over Time Using Tensor-Based Methods. - Kenneth Verstraete; Tom Decroos; Bruno Coussement; Nick Vannieuwenhoven; Jesse Davis (PKDD/ECML Workshops (2), 2019)

Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption. - Ondrej Kuzelka; Jesse Davis (UAI, 2019)

Who Will Win It? An In-game Win Probability Model for Football. - Pieter Robberechts; Jan Van Haaren; Jesse Davis (CoRR, 2019)

Gait Event Detection in Tibial Acceleration Profiles: a Structured Learning Approach. - Pieter Robberechts; Rud Derie; Pieter Van den Berghe; Joeri Gerlo; Dirk De Clercq; Veerle Segers; Jesse Davis (CoRR, 2019)

A general anomaly detection framework for fleet-based condition monitoring of machines. - Kilian Hendrickx; Wannes Meert; Yves Mollet; Johan Gyselinck; Bram Cornelis; Konstantinos C. Gryllias; Jesse Davis (CoRR, 2019)

Guest editorial: special issue on machine learning for soccer. - Daniel Berrar; Philippe Lopes; Jesse Davis; Werner Dubitzky (Mach. Learn., 2019)

The Open International Soccer Database for machine learning. - Werner Dubitzky; Philippe Lopes; Jesse Davis; Daniel Berrar (Mach. Learn., 2019)

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

Multi-directional Rule Set Learning. - Jonas Schouterden; Jesse Davis; Hendrik Blockeel (DS, 2020)

STRiKE: Rule-Driven Relational Learning Using Stratified k-Entailment. - Martin Svatos; Steven Schockaert; Jesse Davis; Ondrej Kuzelka (ECAI, 2020)

VAEP: An Objective Approach to Valuing On-the-Ball Actions in Soccer (Extended Abstract). - Tom Decroos; Lotte Bransen; Jan Van Haaren; Jesse Davis (IJCAI, 2020)

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

SoccerMix: Representing Soccer Actions with Mixture Models. - Tom Decroos; Maaike Van Roy; Jesse Davis (ECML/PKDD (5), 2020)

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

How Data Availability Affects the Ability to Learn Good xG Models. - Pieter Robberechts; Jesse Davis (MLSA@PKDD/ECML, 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)

Additive Tree Ensembles: Reasoning About Potential Instances. - Laurens Devos; Wannes Meert; Jesse Davis (CoRR, 2020)

Learning from positive and unlabeled data: a survey. - Jessa Bekker; Jesse Davis (Mach. Learn., 2020)

Towards the Monitoring of Functional Status in a Free-Living Environment for People with Hip or Knee Osteoarthritis: Design and Evaluation of the JOLO Blended Care App. - Jill Emmerzaal; Arne De Brabandere; Yves Vanrompay; Julie Vranken; Valerie Storms; Liesbet De Baets; Kristoff Corten; Jesse Davis; Ilse Jonkers; Benedicte Vanwanseele; Annick Timmermans (Sensors, 2020)

DTAIDistance. - Wannes Meert; Kilian Hendrickx; Toon van Craenendonck; Pieter Robberechts; Hendrik Blockeel; Jesse Davis (Zenodo, 2020)

Know Your Limits: Machine Learning with Rejection for Vehicle Engineering. - Kilian Hendrickx; Wannes Meert; Bram Cornelis; Jesse Davis (ADMA, 2021)

Mapping probability word problems to executable representations. - Simon Suster; Pieter Fivez; Pietro Totis; Angelika Kimmig; Jesse Davis; Luc De Raedt; Walter Daelemans (EMNLP (1), 2021)

Versatile Verification of Tree Ensembles. - Laurens Devos; Wannes Meert; Jesse Davis (ICML, 2021)

A Bayesian Approach to In-Game Win Probability in Soccer. - Pieter Robberechts; Jan Van Haaren; Jesse Davis (KDD, 2021)

Verifying Tree Ensembles by Reasoning about Potential Instances. - Laurens Devos; Wannes Meert; Jesse Davis (SDM, 2021)

Leaving Goals on the Pitch: Evaluating Decision Making in Soccer. - Maaike Van Roy; Pieter Robberechts; Wen-Chi Yang; Luc De Raedt; Jesse Davis (CoRR, 2021)

Machine Learning in Sports (Dagstuhl Seminar 21411). - Ulf Brefeld; Jesse Davis; Martin Lames; James J. Little (Dagstuhl Reports, 2021)

Evaluation of Automated Hypnogram Analysis on Multi-Scored Polysomnographies. - Dries Van der Plas; Johan Verbraecken; Marc Willemen; Wannes Meert; Jesse Davis (Frontiers Digit. Health, 2021)

Motion Sensor-Based Detection of Outlier Days Supporting Continuous Health Assessment for Single Older Adults. - Marc Mertens; Glen Debard; Jesse Davis; Els Devriendt; Koen Milisen; Jos Tournoy; Tom Croonenborghs; Bart Vanrumste (Sensors, 2021)

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

Unifying Knowledge Base Completion with PU Learning to Mitigate the Observation Bias. - Jonas Schouterden; Jessa Bekker; Jesse Davis; Hendrik Blockeel (AAAI, 2022)

Semi-supervised Change Point Detection Using Active Learning. - Arne De Brabandere; Zhenxiang Cao; Maarten De Vos; Alexander Bertrand; Jesse Davis (DS, 2022)

Elastic Product Quantization for Time Series. - Pieter Robberechts; Wannes Meert; Jesse Davis (DS, 2022)

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 (EBeM@IJCAI, 2022)

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

Looking Beyond the Past: Analyzing the Intrinsic Playing Style of Soccer Teams. - Jeroen Clijmans; Maaike Van Roy; Jesse Davis (ECML/PKDD (6), 2022)

Towards Data-Driven Volatility Modeling with Variational Autoencoders. - Thomas Dierckx; Jesse Davis; Wim Schoutens (PKDD/ECML Workshops (2), 2022)

Bitpaths: Compressing Datasets Without Decreasing Predictive Performance. - Loren Nuyts; Laurens Devos; Wannes Meert; Jesse Davis (PKDD/ECML Workshops (1), 2022)

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

Adversarial Example Detection in Deployed Tree Ensembles. - Laurens Devos; Wannes Meert; Jesse Davis (CoRR, 2022)

Impact of Gender and Feature Set on Machine-Learning-Based Prediction of Lower-Limb Overuse Injuries Using a Single Trunk-Mounted Accelerometer. - Sieglinde Bogaert; Jesse Davis; Sam Van Rossom; Benedicte Vanwanseele (Sensors, 2022)

Can the Output of a Learned Classification Model Monitor a Person's Functional Recovery Status Post-Total Knee Arthroplasty? - Jill Emmerzaal; Arne De Brabandere; Rob van der Straaten; Johan Bellemans; Liesbet De Baets; Jesse Davis; Ilse Jonkers; Annick Timmermans; Benedicte Vanwanseele (Sensors, 2022)

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

un-xPass: Measuring Soccer Player's Creativity. - Pieter Robberechts; Maaike Van Roy; Jesse Davis (KDD, 2023)

Unsupervised Anomaly Detection with Rejection. - Lorenzo Perini; Jesse Davis (NeurIPS, 2023)

Detecting Evasion Attacks in Deployed Tree Ensembles. - Laurens Devos; Lorenzo Perini; Wannes Meert; Jesse Davis (ECML/PKDD (5), 2023)

Semi-supervised Learning from Active Noisy Soft Labels for Anomaly Detection. - Timo Martens; Lorenzo Perini; Jesse Davis (ECML/PKDD (1), 2023)

A novel reject option applied to sleep stage scoring. - Dries Van der Plas; Wannes Meert; Johan Verbraecken; Jesse Davis (SDM, 2023)

How to Allocate your Label Budget? Choosing between Active Learning and Learning to Reject in Anomaly Detection. - Lorenzo Perini; Daniele Giannuzzi; Jesse Davis (CoRR, 2023)

A Markov Framework for Learning and Reasoning About Strategies in Professional Soccer. - Maaike Van Roy; Pieter Robberechts; Wen-Chi Yang; Luc De Raedt; Jesse Davis (J. Artif. Intell. Res., 2023)

Lifted Reasoning for Combinatorial Counting. - Pietro Totis; Jesse Davis; Luc De Raedt; Angelika Kimmig (J. Artif. Intell. Res., 2023)

Robustness Verification of Multi-Class Tree Ensembles. - Laurens Devos; Lorenzo Cascioli; Jesse Davis (AAAI, 2024)

DMON: A Simple Yet Effective Approach for Argument Structure Learning. - Wei Sun 046; Mingxiao Li 002; Jingyuan Sun; Jesse Davis; Marie-Francine Moens (LREC/COLING, 2024)

Safety Verification of Tree-Ensemble Policies via Predicate Abstraction. - Chaahat Jain; Lorenzo Cascioli; Laurens Devos; Marcel Vinzent; Marcel Steinmetz; Jesse Davis; Jörg Hoffmann 001 (ECAI, 2024)

Combining Active Learning and Learning to Reject for Anomaly Detection. - Luca Stradiotti; Lorenzo Perini; Jesse Davis (ECAI, 2024)

Faster Repeated Evasion Attacks in Tree Ensembles. - Lorenzo Cascioli; Laurens Devos; Ondrej Kuzelka; Jesse Davis (NeurIPS, 2024)

Semi-Supervised Isolation Forest for Anomaly Detection. - Luca Stradiotti; Lorenzo Perini; Jesse Davis (SDM, 2024)

Biases in Expected Goals Models Confound Finishing Ability. - Jesse Davis; Pieter Robberechts (CoRR, 2024)

Deep Neural Network Benchmarks for Selective Classification. - Andrea Pugnana; Lorenzo Perini; Jesse Davis; Salvatore Ruggieri (CoRR, 2024)

Computational Approaches to Strategy and Tactics in Sports (Dagstuhl Seminar 24081). - Ulf Brefeld; Jesse Davis; Laura de Jong; Stephanie Kovalchik (Dagstuhl Reports, 2024)

Detecting Epileptic Seizures Using Hand-Crafted and Automatically Constructed EEG Features. - Arne De Brabandere; Christos Chatzichristos; Wim Van Paesschen; Maarten De Vos; Jesse Davis (IEEE Trans. Biomed. Eng., 2024)

Machine learning with a reject option: a survey. - Kilian Hendrickx; Lorenzo Perini; Dries Van der Plas; Wannes Meert; Jesse Davis (Mach. Learn., 2024)

Time-Shifted Transformers for Driver Identification Using Vehicle Data. - Wim Govers; Aras Yurtman; Turgay Aslandere; Nicole Eikelenberg; Wannes Meert; Jesse Davis (IEEE Trans. Intell. Transp. Syst., 2024)

TSFuse: automated feature construction for multiple time series data. - Arne De Brabandere; Tim Op De Beéck; Kilian Hendrickx; Wannes Meert; Jesse Davis (Mach. Learn., 2024)

Methodology and evaluation in sports analytics: challenges, approaches, and lessons learned. - Jesse Davis; Lotte Bransen; Laurens Devos; Arne Jaspers; Wannes Meert; Pieter Robberechts; Jan Van Haaren; Maaike Van Roy (Mach. Learn., 2024)

Mitigating Negative Interference in Multilingual Knowledge Editing through Null-Space Constraints. - Wei Sun 046; Tingyu Qu; Mingxiao Li 002; Jesse Davis; Marie-Francine Moens (ACL (Findings), 2025)

Learning from biased positive-unlabeled data via threshold calibration. - Pawel Teisseyre; Timo Martens; Jessa Bekker; Jesse Davis (AISTATS, 2025)

The When and How of Target Variable Transformations. - Loren Nuyts; Jesse Davis (IDA, 2025)

Generating Explanations in Medical Question-Answering by Expectation Maximization Inference over Evidence. - Wei Sun 046; Mingxiao Li 002; Damien Sileo; Jesse Davis; Marie-Francine Moens (ACM Trans. Comput. Heal., 2025)

Common Data Format (CDF): A Standardized Format for Match-Data in Football (Soccer). - Gabriel Anzer; Kilian Arnsmeyer; Pascal Bauer; Joris Bekkers; Ulf Brefeld; Jesse Davis; Nicolas Evans; Matthias Kempe; Samuel J. Robertson; Joshua Wyatt Smith; Jan Van Haaren (CoRR, 2025)

Stop Guessing: Optimizing Goalkeeper Policies for Soccer Penalty Kicks. - Lotte Bransen; Tim Janssen; Jesse Davis (CoRR, 2025)

Mitigating Negative Interference in Multilingual Sequential Knowledge Editing through Null-Space Constraints. - Wei Sun 046; Tingyu Qu; Mingxiao Li 002; Jesse Davis; Marie-Francine Moens (CoRR, 2025)

What Makes a Dribble Successful? Insights From 3D Pose Tracking Data. - Michiel Schepers; Pieter Robberechts; Jan Van Haaren; Jesse Davis (CoRR, 2025)

Dealing with Uncertainty in Contextual Anomaly Detection. - Luca Bindini; Lorenzo Perini; Stefano Nistri; Jesse Davis; Paolo Frasconi (CoRR, 2025)

Learning to Reject Low-Quality Explanations via User Feedback. - Luca Stradiotti; Dario Pesenti; Stefano Teso; Jesse Davis (CoRR, 2025)

TSelect: selecting relevant and non-redundant channels for multivariate time series classification. - Loren Nuyts; Lorenzo Perini; Jesse Davis (Data Min. Knowl. Discov., 2025)