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
Heri RamampiaroProfessor of Computer Science at the Norwegian University of Science and Technology (NTNU)Verified email at ntnu.no
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-LópezProfessor of Applied Mathematics, 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
Georgios K. PitsilisPhD in Computer ScienceVerified email at ntnu.no
Antonio FernándezSenior Data Scientist in Banking (Cajamar)Verified email at bcc.es
Massimiliano Ruocco, PhDSenior Researcher, Sintef Digital. Adjunct Associate Professor, NTNUVerified email at ntnu.no
Anders Kofod-PetersenPiedBoeuf / NTNUVerified email at kofod-petersen.com
Rafael CabañasUniversity of AlmeríaVerified email at ual.es
Hanen BorchaniSimCorp A/SVerified email at simcorp.com
Tárik S. SalemNorwegian University of Science and Technology (NTNU)Verified email at ntnu.no
Ole MengshoelProfessor of ECE, CMUVerified email at sv.cmu.edu
Ming ZengCarnegie Mellon UniversityVerified email at sv.cmu.edu

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	801	2007
Effective hate-speech detection in Twitter data using recurrent neural networks GK Pitsilis, H Ramampiaro, H Langseth Applied Intelligence 48 (12), 4730-4742, 2018	293	2018
Detecting offensive language in tweets using deep learning GK Pitsilis, H Ramampiaro, H Langseth arXiv preprint arXiv:1801.04433, 2018	204	2018
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	194	2018
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	143	2018
Inference in hybrid Bayesian networks H Langseth, TD Nielsen, R Rumí, A Salmerón Reliability Engineering & System Safety 94 (10), 1499-1509, 2009	137	2009
Classification using hierarchical naive bayes models H Langseth, TD Nielsen Machine learning 63, 135-159, 2006	120	2006
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	108	2001
Mixtures of truncated basis functions H Langseth, TD Nielsen, R Rumı, A Salmerón International Journal of Approximate Reasoning 53 (2), 212-227, 2012	104	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	102	2017
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	94	2017
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	92	2015
Reliability prediction method for safety instrumented systems S Hauge, P Hokstad, H Langseth, K Oien PDS method handbook, 25-27, 2006	82	2006
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	75	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	65	2003
Review of Inference Algorithms for Hybrid Bayesian Networks A Salmerón, R Rumí, H Langseth, TD Nielsen, AL Madsen Journal of Artificial Intelligence Research 63, 799-828, 2018	64	2018
Learning similarity measures from data BM Mathisen, A Aamodt, K Bach, H Langseth Progress in Artificial Intelligence 9 (2), 129-143, 2020	63	2020
Parameter learning in object-oriented Bayesian networks H Langseth, O Bangsø Annals of Mathematics and Artificial Intelligence 32, 221-243, 2001	61	2001
A latent model for collaborative filtering H Langseth, TD Nielsen International Journal of Approximate Reasoning 53 (4), 447-466, 2012	58	2012
Competing risks for repairable systems: A data study H Langseth, BH Lindqvist Journal of Statistical Planning and Inference 136 (5), 1687-1700, 2006	51	2006

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