Jan Van Haaren

According to our database, Jan Van Haaren authored at least 22 papers between 2011 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

Proceedings of the Workshop on AI Evaluation Beyond Metrics co-located with the 31st International Joint Conference on Artificial Intelligence (IJCAI-ECAI 2022), 2022

2021

"Why Would I Trust Your Numbers?" On the Explainability of Expected Values in Soccer.

Jan Van Haaren

CoRR, 2021

A Bayesian Approach to In-Game Win Probability in Soccer.

Pieter Robberechts, Jan Van Haaren, Jesse Davis

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

Player Chemistry: Striving for a Perfectly Balanced Soccer Team.

Lotte Bransen, Jan Van Haaren

CoRR, 2020

VAEP: An Objective Approach to Valuing On-the-Ball Actions in Soccer (Extended Abstract).

Tom Decroos, Lotte Bransen, Jan Van Haaren, Jesse Davis

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Who Will Win It? An In-game Win Probability Model for Football.

Pieter Robberechts, Jan Van Haaren, Jesse Davis

CoRR, 2019

Actions Speak Louder than Goals: Valuing Player Actions in Soccer.

Tom Decroos, Lotte Bransen, Jan Van Haaren, Jesse Davis

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018

Measuring Football Players' On-the-Ball Contributions from Passes During Games.

Lotte Bransen, Jan Van Haaren

Proceedings of the 5th Workshop on Machine Learning and Data Mining for Sports Analytics co-located with 2018 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2018), 2018

Distinguishing Between Roles of Football Players in Play-by-Play Match Event Data.

Bart Aalbers, Jan Van Haaren

Proceedings of the 5th Workshop on Machine Learning and Data Mining for Sports Analytics co-located with 2018 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2018), 2018

Automatic Discovery of Tactics in Spatio-Temporal Soccer Match Data.

Tom Decroos, Jan Van Haaren, Jesse Davis

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2017

Predicting the Potential of Professional Soccer Players.

Ruben Vroonen, Tom Decroos, Jan Van Haaren, Jesse Davis

Proceedings of the 4th Workshop on Machine Learning and Data Mining for Sports Analytics co-located with 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), 2017

STARSS: A Spatio-Temporal Action Rating System for Soccer.

Tom Decroos, Jan Van Haaren, Vladimir Dzyuba, Jesse Davis

Proceedings of the 4th Workshop on Machine Learning and Data Mining for Sports Analytics co-located with 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), 2017

Predicting Soccer Highlights from Spatio-Temporal Match Event Streams.

Tom Decroos, Vladimir Dzyuba, Jan Van Haaren, Jesse Davis

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Relational approaches for learning, transferring and mining ; Relationele benaderingen voor leren, overdragen en mijnen.

Jan Van Haaren

PhD thesis, 2016

Lifted generative learning of Markov logic networks.

Jan Van Haaren, Guy Van den Broeck, Wannes Meert, Jesse Davis

Mach. Learn., 2016

Analyzing Volleyball Match Data from the 2014 World Championships Using Machine Learning Techniques.

Jan Van Haaren, Horesh Ben Shitrit, Jesse Davis, Pascal Fua

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

2015

Automatically Discovering Offensive Patterns in Soccer Match Data.

Jan Van Haaren, Vladimir Dzyuba, Siebe Hannosset, Jesse Davis

Proceedings of the Advances in Intelligent Data Analysis XIV, 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

Proceedings of the Artificial Intelligence in Medicine, 2015

TODTLER: Two-Order-Deep Transfer Learning.

Jan Van Haaren, Andrey Kolobov, Jesse Davis

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2012

Towards an Automated Pattern Selection Procedure in Software Models.

Alexander van Den Berghe, Jan Van Haaren, Stefan Van Baelen, Yolande Berbers, Wouter Joosen

Proceedings of the Late Breaking Papers of the 22nd International Conference on Inductive Logic Programming, 2012

Markov Network Structure Learning: A Randomized Feature Generation Approach.

Jan Van Haaren, Jesse Davis

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011

Relational Learning for Football-Related Predictions.

Jan Van Haaren, Guy Van den Broeck

Proceedings of the Latest Advances in Inductive Logic Programming, 2011