Volgen
Daan Fierens
Daan Fierens
Department of Computer Science, KULeuven
Geverifieerd e-mailadres voor cs.kuleuven.be
Titel
Geciteerd door
Geciteerd door
Jaar
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
4222015
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
1192007
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
1082012
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
842013
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
812005
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
602008
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
402016
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
362015
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
352013
Lifted variable elimination with arbitrary constraints
N Taghipour, D Fierens, J Davis, H Blockeel
Artificial Intelligence and Statistics, 1194-1202, 2012
302012
Constraints for probabilistic logic programming
D Fierens, G Van den Broeck, M Bruynooghe, L De Raedt
Proceedings of the NIPS probabilistic programming workshop 2, 129-174, 2012
242012
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
202006
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
192005
Logical bayesian networks
D Fierens, H Blockeel, J Ramon, M Bruynooghe
Third workshop on multi-relational data mining, 19-30, 2004
182004
ProbLog2: From probabilistic programming to statistical relational learning
J Renkens, D Shterionov, G Van den Broeck, J Vlasselaer, D Fierens, ...
Proc. of NIPS, 1-5, 2012
172012
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
162008
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
102011
Context-specific independence in directed relational probabilistic models and its influence on the efficiency of Gibbs sampling
D Fierens
ECAI 2010, 243-248, 2010
102010
Het systeem kan de bewerking nu niet uitvoeren. Probeer het later opnieuw.
Artikelen 1–20