Follow
Daan Fierens
Daan Fierens
Department of Computer Science, KULeuven
Verified email at cs.kuleuven.be
Title
Cited by
Cited by
Year
Inference and learning in probabilistic logic programs using weighted boolean formulas
D Fierens, G Van den Broeck, J Renkens, D Shterionov, B Gutmann, ...
Theory and Practice of Logic Programming 15 (3), 358-401, 2015
3852015
Mining data from intensive care patients
J Ramon, D Fierens, F Güiza, G Meyfroidt, H Blockeel, M Bruynooghe, ...
Advanced Engineering Informatics 21 (3), 243-256, 2007
1172007
Inference in probabilistic logic programs using weighted CNF's
D Fierens, GV Broeck, I Thon, B Gutmann, L De Raedt
arXiv preprint arXiv:1202.3719, 2012
1062012
Logical Bayesian networks and their relation to other probabilistic logical models
D Fierens, H Blockeel, M Bruynooghe, J Ramon
Inductive Logic Programming: 15th International Conference, ILP 2005, Bonn …, 2005
832005
Lifted variable elimination: Decoupling the operators from the constraint language
N Taghipour, D Fierens, J Davis, H Blockeel
Journal of Artificial Intelligence Research 47, 393-439, 2013
762013
Towards digesting the alphabet-soup of statistical relational learning
L De Raedt, B Demoen, D Fierens, B Gutmann, G Janssens, A Kimmig, ...
NIPS* 2008 Workshop Probabilistic Programming, Date: 2008/12/13-2008/12/13 …, 2008
582008
Instance-level accuracy versus bag-level accuracy in multi-instance learning
G Vanwinckelen, V Tragante Do O, D Fierens, H Blockeel
Data mining and knowledge discovery 30, 313-341, 2016
372016
Shterionov, Bernd Gutmann, Ingo Thon, Gerda Janssens, and Luc De Raedt. Inference and learning in probabilistic logic programs using weighted boolean formulas
D Fierens, G Van den Broeck, J Renkens, D Sht
Theory Pract. Log. Program 15 (3), 358-401, 2015
332015
Completeness results for lifted variable elimination
N Taghipour, D Fierens, G Van den Broeck, J Davis, H Blockeel
Artificial Intelligence and Statistics, 572-580, 2013
312013
Lifted variable elimination with arbitrary constraints
N Taghipour, D Fierens, J Davis, H Blockeel
Artificial Intelligence and Statistics, 1194-1202, 2012
292012
Constraints for probabilistic logic programming
D Fierens, G Van den Broeck, M Bruynooghe, L De Raedt
Proceedings of the NIPS probabilistic programming workshop, 1-4, 2012
242012
A comparison of approaches for learning probability trees
D Fierens, J Ramon, H Blockeel, M Bruynooghe
Machine Learning: ECML 2005: 16th European Conference on Machine Learning …, 2005
212005
The ace data mining system, user’s manual
H Blockeel, L Dehaspe, J Ramon, J Struyf, A Van Assche, C Vens, ...
Katholieke Universiteit Leuven, Belgium, 2006
192006
Logical bayesian networks
D Fierens, H Blockeel, J Ramon, M Bruynooghe
Proceedings of the 3rd international workshop on multi-relational data …, 2004
192004
A comparison of pruning criteria for probability trees
D Fierens, J Ramon, H Blockeel, M Bruynooghe
Machine Learning 78, 251-285, 2010
172010
Generalized ordering-search for learning directed probabilistic logical models
J Ramon, T Croonenborghs, D Fierens, H Blockeel, M Bruynooghe
Machine Learning 70, 169-188, 2008
172008
ProbLog2: From probabilistic programming to statistical relational learning
J Renkens, D Shterionov, G Van den Broeck, J Vlasselaer, D Fierens, ...
Proceedings of the NIPS Probabilistic Programming Workshop, 2012
152012
Three complementary approaches to context aware movie recommendation
H Rahmani, B Piccart, D Fierens, H Blockeel
Proceedings of the Workshop on Context-Aware Movie Recommendation, 57-60, 2010
152010
Instance-level accuracy versus bag-level accuracy in multi-instance learning
V Tragante do O, D Fierens, H Blockeel
Proceedings of the 23rd Benelux conference on artificial intelligence (BNAIC), 8, 2011
92011
Context-Specific Independence in Directed Relational Probabilistic Models and its Influence on the Efficiency of Gibbs Sampling.
D Fierens
ECAI, 243-248, 2010
92010
The system can't perform the operation now. Try again later.
Articles 1–20