Daan Fierens

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Hendrik BlockeelDepartment of Computer Science, KU LeuvenAdresse e-mail validée de cs.kuleuven.be
Guy Van den BroeckProfessor and Samueli Fellow, UCLAAdresse e-mail validée de cs.ucla.edu
Maurice BruynoogheProfessor Em. of Computer Science, KULeuvenAdresse e-mail validée de cs.kuleuven.be
Luc De Raedtprofessor, KU Leuven & guestprofessor, Örebro UniversityAdresse e-mail validée de cs.kuleuven.be
Jesse DavisProfessor, Department of Computer Science, KU LeuvenAdresse e-mail validée de cs.kuleuven.be
Nima TaghipourPostdoctoral Researcher, KU LeuvenAdresse e-mail validée de cs.kuleuven.be
Gerda JanssensProfessor of the Department of Computer Science, KULeuvenAdresse e-mail validée de cs.kuleuven.be
Wannes MeertDTAI, KU LeuvenAdresse e-mail validée de cs.kuleuven.be
Joost VennekensDept. Computer Science, KU LeuvenAdresse e-mail validée de cs.kuleuven.be
Niels LandwehrProfessor, University of HildesheimAdresse e-mail validée de uni-hildesheim.de
Angelika KimmigKU LeuvenAdresse e-mail validée de cs.kuleuven.be
Vinicius TraganteScientific Researcher at deCODE geneticsAdresse e-mail validée de decode.is
Celine Vensprofessor, Katholieke Universiteit LeuvenAdresse e-mail validée de kuleuven.be
bart demoenProfessor of Computer Science, KU LeuvenAdresse e-mail validée de cs.kuleuven.be
Ricardo RochaComputer Science Department, University of PortoAdresse e-mail validée de dcc.fc.up.pt
Gitte VanwinckelenKU Leuven, BelgiumAdresse e-mail validée de cs.kuleuven.be
Tom CroonenborghsKU LeuvenAdresse e-mail validée de khk.be
Jonas VlasselaerAI Expert at DeltaRayAdresse e-mail validée de deltaray.eu
Kristian KerstingProfessor of AI & ML, Technical University of Darmstadt, Co-Director hessian.ai, DFKI, CAIRNE, ELLISAdresse e-mail validée de cs.tu-darmstadt.de
Hossein RahmaniIran Univesity of Science and Technology (IUST)Adresse e-mail validée de iust.ac.ir

Suivre

Daan Fierens

Department of Computer Science, KULeuven

Adresse e-mail validée de cs.kuleuven.be

Artificial Intelligence Machine Learning Probabilistic Models Statistical Relational Learning


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
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	423	2015
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	119	2007
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	108	2012
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	84	2013
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	81	2005
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	60	2008
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	40	2016
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	36	2015
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	35	2013
Lifted variable elimination with arbitrary constraints N Taghipour, D Fierens, J Davis, H Blockeel Artificial Intelligence and Statistics, 1194-1202, 2012	30	2012
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	24	2012
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	20	2006
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	19	2005
Logical bayesian networks D Fierens, H Blockeel, J Ramon, M Bruynooghe Third workshop on multi-relational data mining, 19-30, 2004	18	2004
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	17	2012
A comparison of pruning criteria for probability trees D Fierens, J Ramon, H Blockeel, M Bruynooghe Machine Learning 78, 251-285, 2010	17	2010
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	16	2008
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	15	2010
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	10	2011
Context-specific independence in directed relational probabilistic models and its influence on the efficiency of Gibbs sampling D Fierens ECAI 2010, 243-248, 2010	10	2010

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