Thomas Dyhre Nielsen - Google Scholar Citations

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Helge LangsethNorwegian University of Science and TechnologyVerified email at ntnu.no
Antonio SalmerónUniversity of Almería, SpainVerified email at ual.es
Anders L MadsenCEO at HUGIN EXPERT and Adjunct professor at Aalborg UniversityVerified email at hugin.com
Andres R. MasegosaUniversity of AlmeriaVerified email at ual.es
Rafael RumíAssociate Professor, University of AlmeríaVerified email at ual.es
Ana M. MartínezLarge-Scale Data Specialist, VestasVerified email at vestas.com
Darío Ramos-LópezAssistant Professor, Department of Applied Mathematics, Rey Juan Carlos University, Madrid (Spain)Verified email at ual.es
Manfred JaegerAalborg UniversityVerified email at cs.aau.dk
Antonio FernándezSenior Data Scientist in Banking (BCC - Grupo Cajamar)Verified email at bcc.es
Kim G. LarsenDirector, Professor Aalborg UniversityVerified email at cs.aau.dk
Brian NielsenAssociate Professor of Computer Science, Aalborg UniversityVerified email at cs.aau.dk
Hanen BorchaniSimCorp A/SVerified email at simcorp.com
Rafael CabañasIDSIA - Istituto Dalle Molle di studi sull'Intelligenza ArtificialeVerified email at idsia.ch
Jose Miguel PuertaFull Professor of Computer Science, Castilla-La Mancha UniversityVerified email at uclm.es
Manuel LuqueUNEDVerified email at dia.uned.es
Prakash P. ShenoyUniversity of Kansas School of BusinessVerified email at ku.edu
Jacinto AriasPhD Student, University of Castilla-La ManchaVerified email at uclm.es
Concha BielzaProfessor of Statistics and Operations ResearchVerified email at fi.upm.es
Gherardo VarandoDepartment of Mathematical Sciences, Univeristy of CopenhagenVerified email at math.ku.dk
Juan L. MateoDepartamento de Informática, Universidad de OviedoVerified email at uniovi.es

Thomas Dyhre Nielsen

Aalborg University

Verified email at cs.aau.dk - Homepage

Machine learning data mining Bayesian networks influence diagrams


Title	Cited by	Year
Bayesian networks and decision graphs TD Nielsen, FV Jensen Springer Science & Business Media, 2009	6040	2009
Inference in hybrid Bayesian networks H Langseth, TD Nielsen, R Rumí, A Salmerón Reliability Engineering & System Safety 94 (10), 1499-1509, 2009	102	2009
Classification using hierarchical naive bayes models H Langseth, TD Nielsen Machine learning 63 (2), 135-159, 2006	84	2006
Welldefined decision scenarios TD Nielsen, FV Jensen Proceedings of the Fifteenth conference on Uncertainty in artificial …, 1999	83	1999
Mixtures of truncated basis functions H Langseth, TD Nielsen, R Rumı, A Salmerón International Journal of Approximate Reasoning 53 (2), 212-227, 2012	69	2012
Fusion of domain knowledge with data for structural learning in object oriented domains H Langseth, TD Nielsen Journal of Machine Learning Research 4 (Jul), 339-368, 2003	64	2003
Sequential influence diagrams: A unified asymmetry framework FV Jensen, TD Nielsen, PP Shenoy International Journal of Approximate Reasoning 42 (1-2), 101-118, 2006	52	2006
Learning a decision maker's utility function from (possibly) inconsistent behavior TD Nielsen, FV Jensen Artificial Intelligence 160 (1-2), 53-78, 2004	50	2004
Adapting Bayes network structures to non-stationary domains SH Nielsen, TD Nielsen International Journal of Approximate Reasoning 49 (2), 379-397, 2008	49	2008
Latent variable discovery in classification models NL Zhang, TD Nielsen, FV Jensen Artificial Intelligence in Medicine 30 (3), 283-299, 2004	48	2004
A latent model for collaborative filtering H Langseth, TD Nielsen International Journal of Approximate Reasoning 53 (4), 447-466, 2012	44	2012
Learning probabilistic automata for model checking H Mao, Y Chen, M Jaeger, TD Nielsen, KG Larsen, B Nielsen 2011 Eighth International Conference on Quantitative Evaluation of Systems …, 2011	42	2011
Learning mixtures of truncated basis functions from data H Langseth, TD Nielsen, I Pérez-Bernabé, A Salmerón International Journal of Approximate Reasoning 55 (4), 940-956, 2014	39*	2014
Parameter estimation and model selection for mixtures of truncated exponentials H Langseth, TD Nielsen, R Rumı, A Salmerón International Journal of Approximate Reasoning 51 (5), 485-498, 2010	39	2010
A parallel algorithm for Bayesian network structure learning from large data sets AL Madsen, F Jensen, A Salmerón, H Langseth, TD Nielsen Knowledge-Based Systems 117, 46-55, 2017	35	2017
Sensitivity analysis in influence diagrams TD Nielsen, FV Jensen IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and …, 2003	34	2003
Representing and solving asymmetric Bayesian decision problems TD Nielsen, FV Jensen arXiv preprint arXiv:1301.3879, 2013	31	2013
Dynamic decision making without expected utility: An operational approach TD Nielsen, JY Jaffray European Journal of Operational Research 169 (1), 226-246, 2006	26	2006
Latent classification models H Langseth, TD Nielsen Machine Learning 59 (3), 237-265, 2005	26	2005
Learning Markov decision processes for model checking H Mao, Y Chen, M Jaeger, TD Nielsen, KG Larsen, B Nielsen arXiv preprint arXiv:1212.3873, 2012	23	2012

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