Thomas Dyhre Nielsen

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	All	Since 2016
Citations	8194	2380
h-index	23	16
i10-index	46	29

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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 FernándezData Scientist in Banking (Cajamar) y Profesor Sustituto Interino (Universidad de Almería)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 Puerta (ORCID:0000-000...Professor of Computer Science, Castilla-La Mancha UniversityVerified email at uclm.es
Manuel Luque (ORCID:0000-0003-30...UNEDVerified 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
Juan L. Mateo (ORCID:0000-0001-99...Department of Computing Systems, University of OviedoVerified email at uniovi.es
Gherardo VarandoUniversitat de ValènciaVerified email at uv.es

Thomas Dyhre Nielsen

Aalborg University

Verified email at cs.aau.dk - Homepage

Machine learning data mining Bayesian networks influence diagrams


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Bayesian networks and decision graphs TD Nielsen, FV Jensen Springer Science & Business Media, 2009	6500	2009
Inference in hybrid Bayesian networks H Langseth, TD Nielsen, R Rumí, A Salmerón Reliability Engineering & System Safety 94 (10), 1499-1509, 2009	110	2009
Classification using hierarchical naive bayes models H Langseth, TD Nielsen Machine learning 63 (2), 135-159, 2006	101	2006
Welldefined decision scenarios TD Nielsen, FV Jensen arXiv preprint arXiv:1301.6729, 2013	83	2013
Mixtures of truncated basis functions H Langseth, TD Nielsen, R Rumı, A Salmerón International Journal of Approximate Reasoning 53 (2), 212-227, 2012	76	2012
Fusion of domain knowledge with data for structural learning in object oriented domains H Langseth, TD Nielsen The Journal of Machine Learning Research 4, 339-368, 2003	64	2003
Learning a decision maker's utility function from (possibly) inconsistent behavior TD Nielsen, FV Jensen Artificial Intelligence 160 (1-2), 53-78, 2004	58	2004
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	56	2017
Sequential influence diagrams: A unified asymmetry framework FV Jensen, TD Nielsen, PP Shenoy International Journal of Approximate Reasoning 42 (1-2), 101-118, 2006	55	2006
Latent variable discovery in classification models NL Zhang, TD Nielsen, FV Jensen Artificial Intelligence in Medicine 30 (3), 283-299, 2004	54	2004
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	53	2011
Adapting Bayes network structures to non-stationary domains SH Nielsen, TD Nielsen International Journal of Approximate Reasoning 49 (2), 379-397, 2008	53	2008
A latent model for collaborative filtering H Langseth, TD Nielsen International Journal of Approximate Reasoning 53 (4), 447-466, 2012	49	2012
Representing and solving asymmetric decision problems TD Nielsen, FV Jensen International Journal of Information Technology & Decision Making 2 (02 …, 2003	45	2003
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	42*	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	42	2010
Sensitivity analysis in influence diagrams TD Nielsen, FV Jensen IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and …, 2003	35	2003
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	29	2012
Learning deterministic probabilistic automata from a model checking perspective H Mao, Y Chen, M Jaeger, TD Nielsen, KG Larsen, B Nielsen Machine Learning 105 (2), 255-299, 2016	28	2016
Probabilistic decision graphs for optimization under uncertainty FV Jensen, TD Nielsen 4OR 9 (1), 1-28, 2011	28	2011

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