Daan Fierens

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Hendrik BlockeelDepartment of Computer Science, KU LeuvenEmail confirmado em cs.kuleuven.be
Maurice BruynoogheProfessor Em. of Computer Science, KULeuvenEmail confirmado em cs.kuleuven.be
Guy Van den BroeckProfessor and Samueli Fellow, UCLAEmail confirmado em cs.ucla.edu
Luc De Raedtprofessor, KU Leuven & guestprofessor, Örebro UniversityEmail confirmado em cs.kuleuven.be
Jesse DavisProfessor, Department of Computer Science, KU LeuvenEmail confirmado em cs.kuleuven.be
Nima TaghipourPostdoctoral Researcher, KU LeuvenEmail confirmado em cs.kuleuven.be
Gerda JanssensProfessor of the Department of Computer Science, KULeuvenEmail confirmado em cs.kuleuven.be
Wannes MeertDTAI, KU LeuvenEmail confirmado em cs.kuleuven.be
Joost VennekensVrije Universiteit BrusselEmail confirmado em vub.be
Niels LandwehrProfessor, University of HildesheimEmail confirmado em uni-hildesheim.de
Angelika KimmigKU LeuvenEmail confirmado em cs.kuleuven.be
Vinicius TraganteScientific Researcher at deCODE geneticsEmail confirmado em decode.is
Celine Vensprofessor, Katholieke Universiteit LeuvenEmail confirmado em kuleuven.be
bart demoenProfessor of Computer Science, KU LeuvenEmail confirmado em cs.kuleuven.be
Ricardo RochaComputer Science Department, University of PortoEmail confirmado em dcc.fc.up.pt
Tom CroonenborghsKU LeuvenEmail confirmado em khk.be
Gitte VanwinckelenKU Leuven, BelgiumEmail confirmado em cs.kuleuven.be
Jonas VlasselaerAI Expert at DeltaRayEmail confirmado em deltaray.eu
Kristian KerstingProfessor of AI & ML, Technical University of Darmstadt, Co-Director hessian.ai, DFKI, CAIRNE, ELLISEmail confirmado em cs.tu-darmstadt.de
Hossein RahmaniIran Univesity of Science and Technology (IUST)Email confirmado em iust.ac.ir

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Daan Fierens

Department of Computer Science, KULeuven

Email confirmado em cs.kuleuven.be

Artificial Intelligence Machine Learning Probabilistic Models Statistical Relational Learning


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
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	427	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	122	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	114	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	85	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	85	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	63	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	37	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, 1-4, 2012	26	2012
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	21	2005
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	19	2006
Logical bayesian networks D Fierens, H Blockeel, J Ramon, M Bruynooghe Proceedings of the 3rd international workshop on multi-relational data …, 2004	19	2004
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	18	2012
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	18	2008
A comparison of pruning criteria for probability trees D Fierens, J Ramon, H Blockeel, M Bruynooghe Machine Learning 78, 251-285, 2010	17	2010
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
Learning directed probabilistic logical models: Ordering-search versus structure-search D Fierens, J Ramon, M Bruynooghe, H Blockeel Machine Learning: ECML 2007: 18th European Conference on Machine Learning …, 2007	11	2007
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

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