Thomas Dyhre Nielsen

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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 AalborgVerified email at cs.aau.dk
Rafael RumíProfessor, University of AlmeríaVerified email at ual.es
Ana M. MartínezJoint Research Center, European CommissionVerified email at ec.europa.eu
Darío Ramos-LópezAssistant Professor, Department of Mathematics, University of Almería, Almería (Spain)Verified email at ual.es
Manfred JaegerAalborg UniversityVerified email at cs.aau.dk
Kim G. LarsenDirector, Professor Aalborg UniversityVerified email at cs.aau.dk
Antonio FernándezSenior Data Scientist in Banking (Cajamar)Verified email at bcc.es
Brian NielsenAssociate Professor of Computer Science, Aalborg UniversityVerified email at cs.aau.dk
Hanen BorchaniSimCorp A/SVerified email at simcorp.com
Rafael CabañasUniversity of AlmeríaVerified email at ual.es
Prakash P. ShenoyUniversity of Kansas School of BusinessVerified email at ku.edu
Jose Miguel Puerta (ORCID:0000-000...Professor of Computer Science, Castilla-La Mancha UniversityVerified email at uclm.es
Manuel Luque (ORCID: 0000-0003-30...Universidad Nacional de Educación a Distancia (UNED). Madrid. SpainVerified email at ccia.uned.es
Jacinto AriasPhD Student, University of Castilla-La ManchaVerified email at uclm.es
Concha BielzaProfessor of Statistics and Operations Research, Technical University of MadridVerified email at fi.upm.es
Juan L. Mateo (ORCID:0000-0001-99...Department of Computer Science, 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 FV Jensen, TD Nielsen Springer, 2007	7094	2007
Inference in hybrid Bayesian networks H Langseth, TD Nielsen, R Rumí, A Salmerón Reliability Engineering & System Safety 94 (10), 1499-1509, 2009	120	2009
Classification using hierarchical naive Bayes models H Langseth, TD Nielsen Machine learning 63 (2), 135-159, 2006	106	2006
Mixtures of truncated basis functions H Langseth, TD Nielsen, R Rumı, A Salmerón International Journal of Approximate Reasoning 53 (2), 212-227, 2012	95	2012
Welldefined decision scenarios TD Nielsen, FV Jensen arXiv preprint arXiv:1301.6729, 2013	91	2013
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	82	2017
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	70	2003
Learning a decision maker's utility function from (possibly) inconsistent behavior TD Nielsen, FV Jensen Artificial Intelligence 160 (1-2), 53-78, 2004	61	2004
Adapting Bayes network structures to non-stationary domains SH Nielsen, TD Nielsen International Journal of Approximate Reasoning 49 (2), 379-397, 2008	60	2008
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	59	2011
Latent variable discovery in classification models NL Zhang, TD Nielsen, FV Jensen Artificial intelligence in medicine 30 (3), 283-299, 2004	55	2004
A latent model for collaborative filtering H Langseth, TD Nielsen International Journal of Approximate Reasoning 53 (4), 447-466, 2012	54	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	47	2016
Representing and solving asymmetric decision problems TD Nielsen, FV Jensen International Journal of Information Technology & Decision Making 2 (02 …, 2003	47	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	46*	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	43	2010
Sequential influence diagrams: A unified asymmetry framework FV Jensen, TD Nielsen, PP Shenoy International Journal of Approximate Reasoning 42 (1-2), 101-118, 2006	41	2006
Sensitivity analysis in influence diagrams TD Nielsen, FV Jensen IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and …, 2003	37	2003
TAPAAL and reachability analysis of P/T nets JF Jensen, T Nielsen, LK Oestergaard, J Srba Transactions on Petri Nets and Other Models of Concurrency XI, 307-318, 2016	34	2016
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	34	2012

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