Seguir
Jan Van Haaren
Jan Van Haaren
Club Brugge and KU Leuven
Dirección de correo verificada de cs.kuleuven.be - Página principal
Título
Citado por
Citado por
Año
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
2662019
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
952018
Markov network structure learning: A randomized feature generation approach
J Van Haaren, J Davis
Proceedings of the AAAI Conference on Artificial Intelligence 26 (1), 1148-1154, 2012
952012
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
692017
Lifted generative learning of Markov logic networks
J Van Haaren, G Van den Broeck, W Meert, J Davis
Machine Learning 103, 27-55, 2016
502016
Measuring football players’ on-the-ball contributions from passes during games
L Bransen, J Van Haaren
Machine Learning and Data Mining for Sports Analytics: 5th International …, 2019
422019
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
412019
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
382019
Automatically discovering offensive patterns in soccer match data
J Van Haaren, V Dzyuba, S Hannosset, J Davis
Advances in Intelligent Data Analysis XIV: 14th International Symposium, IDA …, 2015
382015
VAEP: an objective approach to valuing on-the-ball actions in soccer
T Decroos, L Bransen, J Van Haaren, J Davis
Proceedings of the twenty-ninth international joint conference on artificial …, 2020
312020
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
312016
TODTLER: Two-Order-Deep Transfer Learning
J Van Haaren, A Kolobov, J Davis
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence …, 2015
312015
Distinguishing between roles of football players in play-by-play match event data
B Aalbers, J Van Haaren
Machine Learning and Data Mining for Sports Analytics: 5th International …, 2019
302019
Qualitative spatial reasoning for soccer pass prediction
V Vercruyssen, L De Raedt, J Davis
CEUR Workshop Proceedings 1842, 2016
302016
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
292017
Player chemistry: Striving for a perfectly balanced soccer team
L Bransen, J Van Haaren
arXiv preprint arXiv:2003.01712, 2020
282020
Relational learning for football-related predictions
J Van Haaren, G Van den Broeck
Latest advances in inductive logic programming, 237-244, 2015
272015
A bayesian approach to in-game win probability in soccer
P Robberechts, J Van Haaren, J Davis
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
232021
Machine learning and data mining for sports analytics
U Brefeld, J Davis, J Van Haaren, A Zimmermann
Cham: Springer, 2018
232018
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
232017
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20