| Markov network structure learning: A randomized feature generation approach J Van Haaren, J Davis Proceedings of the AAAI Conference on Artificial Intelligence 26 (1), 2012 | 69 | 2012 |
| Actions speak louder than goals: Valuing player actions in soccer T Decroos, L Bransen, J Van Haaren, J Davis Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 56 | 2019 |
| Predicting soccer highlights from spatio-temporal match event streams T Decroos, V Dzyuba, J Van Haaren, J Davis Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 43 | 2017 |
| Automatically discovering offensive patterns in soccer match data J Van Haaren, V Dzyuba, S Hannosset, J Davis International Symposium on Intelligent Data Analysis, 286-297, 2015 | 31 | 2015 |
| Lifted generative learning of Markov logic networks J Van Haaren, G Van den Broeck, W Meert, J Davis Machine Learning 103 (1), 27-55, 2016 | 29 | 2016 |
| Automatic discovery of tactics in spatio-temporal soccer match data T Decroos, J Van Haaren, J Davis Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 28 | 2018 |
| Analyzing volleyball match data from the 2014 World Championships using machine learning techniques J Van Haaren, H Ben Shitrit, J Davis, P Fua Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016 | 21 | 2016 |
| Measuring football players’ on-the-ball contributions from passes during games L Bransen, J Van Haaren International Workshop on Machine Learning and Data Mining for Sports …, 2018 | 19 | 2018 |
| STARSS: a spatio-temporal action rating system for soccer T Decroos, J Van Haaren, V Dzyuba, J Davis Machine Learning and Data Mining for Sports Analytics ECML/PKDD 2017 …, 2017 | 18 | 2017 |
| TODTLER: Two-Order-Deep Transfer Learning J Van Haaren, A Kolobov, J Davis Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence …, 2015 | 16 | 2015 |
| Relational learning for football-related predictions J Van Haaren, G Van den Broeck Latest advances in inductive logic programming, 237-244, 2015 | 16 | 2015 |
| Measuring soccer players’ contributions to chance creation by valuing their passes L Bransen, J Van Haaren, M van de Velden Journal of Quantitative Analysis in Sports 15 (2), 97-116, 2019 | 13 | 2019 |
| Choke or Shine? Quantifying Soccer Players' Abilities to Perform Under Mental Pressure L Bransen, P Robberechts, J Van Haaren, J Davis Proceedings of the 13th MIT Sloan Sports Analytics Conference, 1-25, 2019 | 12 | 2019 |
| Strategy discovery in professional soccer match data J Van Haaren, S Hannosset, J Davis Proceedings of the KDD-16 Workshop on Large-Scale Sports Analytics, 1-4, 2016 | 12 | 2016 |
| Predicting the potential of professional soccer players R Vroonen, T Decroos, J Van Haaren, J Davis Proceedings of the 4th Workshop on Machine Learning and Data Mining for …, 2017 | 9 | 2017 |
| Predicting the final league tables of domestic football leagues J Van Haaren, J Davis Proceedings of the 5th international conference on mathematics in sport, 202-207, 2015 | 9 | 2015 |
| Mining hierarchical pathology data using inductive logic programming TO De Beéck, A Hommersom, J Van Haaren, M van der Heijden, J Davis, ... Conference on Artificial Intelligence in Medicine in Europe, 76-85, 2015 | 8 | 2015 |
| Who will win it? An in-game win probability model for football P Robberechts, J Van Haaren, J Davis arXiv preprint arXiv:1906.05029, 2019 | 7 | 2019 |
| Exploring disease interactions using Markov networks J Van Haaren, J Davis, M Lappenschaar, A Hommersom Proceedings of the AAAI-13 Workshop on Expanding the Boundaries of Health …, 2013 | 7 | 2013 |
| Tractable learning of liftable Markov logic networks J Van Haaren, G Van den Broeck, W Meert, J Davis Proceedings of the ICML-14 Workshop on Learning Tractable Probabilistic …, 2014 | 5 | 2014 |
Jesse DavisProfessor, Department of Computer Science, KU LeuvenVerified email at cs.kuleuven.be
