Jan Van Haaren
Jan Van Haaren
SciSports and KU Leuven
Verified email at cs.kuleuven.be - Homepage
Title
Cited by
Cited by
Year
Markov network structure learning: A randomized feature generation approach
J Van Haaren, J Davis
Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012
632012
Predicting soccer highlights from spatio-temporal match event streams
T Decroos, V Dzyuba, J Van Haaren, J Davis
Thirty-First AAAI Conference on Artificial Intelligence, 2017
372017
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
342019
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
282016
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
262015
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
182016
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
162017
TODTLER: Two-Order-Deep Transfer Learning
J Van Haaren, A Kolobov, J Davis
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence …, 2015
162015
Relational learning for football-related predictions
J Van Haaren, G Van den Broeck
Latest advances in inductive logic programming, 237-244, 2015
162015
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
152018
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
122018
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
112016
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
102019
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
82015
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
82015
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
72019
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
72017
Exploring disease interactions using Markov networks
J Van Haaren, J Davis, M Lappenschaar, A Hommersom
Workshops at the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013
72013
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
52019
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
52014
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Articles 1–20