Helge Langseth

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Thomas Dyhre NielsenAalborg UniversityVerified email at cs.aau.dk
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
Heri RamampiaroProfessor of Computer Science at the Norwegian University of Science and Technology (NTNU)Verified email at ntnu.no
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
Agnar AamodtProfessor Emeritus, Norwegian University of Science and TechnologyVerified email at ntnu.no
Bo LindqvistNorwegian University of Science and TechnologyVerified email at ntnu.no
Luigi PortinaleProfessor of Computer Science, Universita' del Piemonte OrientaleVerified email at unipmn.it
Antonio FernándezSenior Data Scientist in Banking (Cajamar)Verified email at bcc.es
Georgios K. PitsilisPhD in Computer ScienceVerified email at ntnu.no
Hanen BorchaniSimCorp A/SVerified email at simcorp.com
Anders Kofod-PetersenPiedBoeuf / NTNUVerified email at kofod-petersen.com
Massimiliano Ruocco, PhDSenior Researcher, Sintef Digital. Adjunct Associate Professor, NTNUVerified email at ntnu.no
Rafael CabañasUniversity of AlmeríaVerified email at ual.es
Hai Thanh NguyenResearch scientist at Telenor ResearchVerified email at ntnu.no
Tárik S. SalemNorwegian University of Science and Technology (NTNU)Verified email at ntnu.no
Basant AgarwalIndian Institute of Information Technology Kota (IIIT Kota)Verified email at iiitkota.ac.in

Helge Langseth

Norwegian University of Science and Technology

Verified email at ntnu.no - Homepage

Bayesian networks Variational Inference Machine Learning Time series analysis


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Bayesian networks in reliability H Langseth, L Portinale Reliability Engineering & System Safety 92 (1), 92-108, 2007	690	2007
Detecting offensive language in tweets using deep learning GK Pitsilis, H Ramampiaro, H Langseth arXiv preprint arXiv:1801.04433, 2018	134	2018
Effective hate-speech detection in Twitter data using recurrent neural networks GK Pitsilis, H Ramampiaro, H Langseth Applied Intelligence 48 (12), 4730-4742, 2018	125	2018
Inference in hybrid Bayesian networks H Langseth, TD Nielsen, R Rumí, A Salmerón Reliability Engineering & System Safety 94 (10), 1499-1509, 2009	118	2009
Classification using hierarchical naive Bayes models H Langseth, TD Nielsen Machine learning 63 (2), 135-159, 2006	105	2006
A deep network model for paraphrase detection in short text messages B Agarwal, H Ramampiaro, H Langseth, M Ruocco Information Processing & Management 54 (6), 922-937, 2018	100	2018
The SACSO methodology for troubleshooting complex systems FV Jensen, U Kjærulff, B Kristiansen, H Langseth, C Skaanning, J Vomlel, ... AI EDAM 15 (4), 321-333, 2001	98	2001
Understanding and improving recurrent networks for human activity recognition by continuous attention M Zeng, H Gao, T Yu, OJ Mengshoel, H Langseth, I Lane, X Liu Proceedings of the 2018 ACM international symposium on wearable computers, 56-63, 2018	88	2018
Mixtures of truncated basis functions H Langseth, TD Nielsen, R Rumı, A Salmerón International Journal of Approximate Reasoning 53 (2), 212-227, 2012	85	2012
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	74	2017
Reliability prediction method for safety instrumented systems S Hauge, P Hokstad, H Langseth, K Oien PDS method handbook, 25-27, 2006	73	2006
Short-term load forecasting with seasonal decomposition using evolution for parameter tuning BA Høverstad, A Tidemann, H Langseth, P Öztürk IEEE Transactions on Smart Grid 6 (4), 1904-1913, 2015	71	2015
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	68	2003
A maintenance model for components exposed to several failure mechanisms and imperfect repair H Langseth, BH Lindqvist Mathematical and Statistical Methods in Reliability, 415-430, 2003	61	2003
Parameter learning in object-oriented Bayesian networks H Langseth, O Bangsø Annals of Mathematics and Artificial Intelligence 32 (1), 221-243, 2001	56	2001
A latent model for collaborative filtering H Langseth, TD Nielsen International Journal of Approximate Reasoning 53 (4), 447-466, 2012	51	2012
Competing risks for repairable systems: A data study H Langseth, BH Lindqvist Journal of Statistical Planning and Inference 136 (5), 1687-1700, 2006	48	2006
Modelling of dependence between critical failure and preventive maintenance: The repair alert model BH Lindqvist, B Støve, H Langseth Journal of Statistical Planning and Inference 136 (5), 1701-1717, 2006	47	2006
Inter-session modeling for session-based recommendation M Ruocco, OSL Skrede, H Langseth Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems, 24-31, 2017	46	2017
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

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