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Langseth, Helge Author

Open Access

What predicts citation counts and translational impact in headache research? A machine learning analysis

  • Danelakis A.
  • Langseth H.
  • Nachev P.
  • Nelson A.
  • Bjørk M.H.
  • Matharu M.S.
  • Tronvik E.
  • May A.
  • Stubberud A.
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Cephalalgia : an international journal of headache - 1/5/2024

10.1177/03331024241251488

Cite count:
Open Access

Consumer-side fairness in recommender systems: a systematic survey of methods and evaluation

  • Vassøy B.
  • Langseth H.

Artificial Intelligence Review - 1/4/2024

10.1007/s10462-023-10663-5

Cite count:
  • CiteScore: 23 (2022)
  • SJR: 2.49 (2022
  • SNIP: 4.347 (2022

Applying Bayesian optimization to predict parameters in a time-domain model for cross-flow vortex-induced vibrations

  • Andersen M.L.
  • Sævik S.
  • Wu J.
  • Leira B.J.
  • Langseth H.

Marine Structures - 1/3/2024

10.1016/j.marstruc.2023.103571

Cite count:
  • CiteScore: 7.6 (2022)
  • SJR: 1.228 (2022
  • SNIP: 2.239 (2022

Deep Contextual Grid Triplet Network for Context-Aware Recommendation

  • Sofia Aftab
  • Heri Ramampiaro
  • Helge Langseth
  • Massimiliano Ruocco

IEEE Access - 1/1/2023

10.1109/access.2023.3310470

Cite count:

Machine Learning in Financial Market Surveillance: A Survey

  • Tiwari S.
  • Ramampiaro H.
  • Langseth H.

IEEE Access - 1/1/2021

10.1109/access.2021.3130843

Cite count:
  • JCR Impact Factor: 3.476 (2021)
  • JCR 5-year Impact Factor: 3.758
  • JCR Categories: COMPUTER SCIENCE, INFORMATION SYSTEMS
Open Access

Probabilistic Models with Deep Neural Networks

  • Andrés R. Masegosa
  • Rafael Cabañas De Paz
  • Helge Langseth
  • Thomas Dyhre Nielsen
  • Antonio Salmerón Cerdán

Entropy - 1/01/2021

10.3390/e23010117

Cite count: 4 (Web of Science)
  • JCR Quartile: Q2 (2021)
  • JCR Impact Factor: 2.738 (2022)
  • Category normalized Impact: 0.156 (2021)
  • CiteScore: 4 (2020)
  • SJR: 0.468 (2020
  • SNIP: 1.059 (2020
  • JCR 5-year Impact Factor: 2.642
  • JCR Categories: PHYSICS, MULTIDISCIPLINARY
Open Access

Variational Inference over Nonstationary Data Streams for Exponential Family Models

  • Andrés R. Masegosa
  • Darío Ramos-López
  • Antonio Salmerón
  • Helge Langseth
  • Thomas D. Nielsen

Mathematics - 3/11/2020

10.3390/math8111942

Cite count: 8 (Web of Science) 2 (Scopus)
  • JCR Quartile: Q1 (2020)
  • JCR Impact Factor: 2.258 (2022)
  • Category normalized Impact: 2.467 (2020)
  • JCR 5-year Impact Factor: 2.165
  • JCR Categories: MATHEMATICS

Analyzing concept drift: A case study in the financial sector

  • Masegosa A.R.
  • Martínez A.M.
  • Ramos-López D.
  • Langseth H.
  • Nielsen T.D.
  • Salmerón A.

Intelligent Data Analysis - 21/05/2020

10.3233/ida-194515

Cite count: 7 (Web of Science) 1 (Scopus)
  • JCR Quartile: Q4 (2020)
  • JCR Impact Factor: 0.86 (2022)
  • Category normalized Impact: 0.379 (2020)
  • CiteScore: 1.7 (2020)
  • SJR: 0.231 (2020
  • SNIP: 0.527 (2020
  • JCR 5-year Impact Factor: 0.894
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Application of data-driven models in the analysis of marine power systems

  • Swider A.
  • Langseth H.
  • Pedersen E.

Applied Ocean Research - 1/11/2019

10.1016/j.apor.2019.101934

Cite count: 4 (Web of Science) 3 (Scopus)
  • SJR Quartile: Q1
  • JCR Impact Factor: 2.753 (2019)
  • CiteScore: 4.5 (2020)
  • SJR: 1.288 (2019
  • SNIP: 2.113 (2019
  • JCR 5-year Impact Factor: 2.935
  • JCR Categories: ENGINEERING, OCEAN
  • SJR Categories: Ocean Engineering (Q1)

Learning similarity measures from data

  • Mathisen B.
  • Aamodt A.
  • Bach K.
  • Langseth H.

Progress in Artificial Intelligence - 1/1/2019

10.1007/s13748-019-00201-2

Cite count: 21 (Web of Science) 15 (Scopus)
  • SJR Quartile: Q2
  • CiteScore: 3.4 (2020)
  • SJR: 0.322 (2020
  • SNIP: 0.746 (2020
  • SJR Categories: Artificial Intelligence (Q2)

Learning hybrid bayesian networks using mixtures of truncated basis functions. Aprendizaje de redes bayesianas híbridas con mixturas de funciones base truncadas

  • Inmaculada Pérez-Bernabé
  • Antonio Salmerón Cerdán
  • Helge Langseth

2015

Cite count:
  • Dialnet

Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions

  • Langseth H.
  • Nielsen T.
  • Rumí R.
  • Salmerón A.

Proceedings of the Sixth European Workshop on Probabilistic Graphical Models - 1/12/2012

Cite count: 11 (Scopus)
  • SJR Categories: Statistics and Probability

Bayesian networks in reliability: The good, the bad, and the ugly

  • Langseth H.

Advances in Mathematical Modeling for Reliability - 1/5/2008

Cite count: 14 (Scopus)

Applications of Bayesian networks in reliability analysis

  • Langseth H.
  • Portinale L.

Bayesian Network Technologies: Applications and Graphical Models - 1/12/2007

10.4018/978-1-59904-141-4.ch005

Cite count: 7 (Scopus)
Open Access

Modeling concept drift: A probabilistic graphical model based approach

  • Borchani H.
  • Martínez A.
  • Masegosa A.
  • Langseth H.
  • Nielsen T.
  • Salmerón A.
  • Fernández A.
  • Madsen A.
  • Sáez R.
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 1/1/2015

10.1007/978-3-319-24465-5_7

Cite count: 13 (Web of Science) 14 (Scopus)
  • JCR Impact Factor: 15.491 (2022)
  • Category normalized Impact: 1.609 (2015)
  • CiteScore: 1.8 (2020)
  • SJR: 0.369 (2015
  • SNIP: 0.708 (2015
Open Access

MPE inference in conditional linear gaussian networks

  • Salmerón A.
  • Rumí R.
  • Langseth H.
  • Madsen A.
  • Nielsen T.

Symbolic and Quantitative Approaches to Reasoning with Uncertainty - 1/1/2015

10.1007/978-3-319-20807-7_37

Cite count: 4 (Scopus)
  • CiteScore: 1.8 (2020)
  • SJR: 0.369 (2015
  • SNIP: 0.708 (2015
Open Access

Parallel importance sampling in conditional linear Gaussian networks

  • Salmerón A.
  • Ramos-López D.
  • Borchani H.
  • Martínez A.
  • Masegosa A.
  • Fernández A.
  • Langseth H.
  • Madsen A.
  • Nielsen T.
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Advances in Artificial Intelligence - 1/1/2015

10.1007/978-3-319-24598-0_4

Cite count: 6 (Web of Science) 7 (Scopus)
  • Category normalized Impact: 0.767 (2015)
  • CiteScore: 1.8 (2020)
  • SJR: 0.369 (2015
  • SNIP: 0.708 (2015
Open Access

A new method for vertical parallelisation of TAN learning based on balanced incomplete block designs

  • Madsen A.
  • Jensen F.
  • Salmerón A.
  • Karlsen M.
  • Langseth H.
  • Nielsen T.

Proceedings of the 7th European Workshop on Probabilistic Graphical Models - 1/1/2014

10.1007/978-3-319-11433-0_20

Cite count: 9 (Web of Science) 10 (Scopus)
  • Category normalized Impact: 0.839 (2014)
  • CiteScore: 1.8 (2020)
  • SJR: 0.354 (2014
  • SNIP: 0.753 (2014
Open Access

Learning to rank for personalised fashion recommender systems via implicit feedback

  • Nguyen H.
  • Almenningen T.
  • Havig M.
  • Schistad H.
  • Kofod-Petersen A.
  • Langseth H.
  • Ramampiaro H.
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 1/1/2014

10.1007/978-3-319-13817-6_6

Cite count: 11 (Scopus)
  • CiteScore: 1.8 (2020)
  • SJR: 0.354 (2014
  • SNIP: 0.753 (2014

Effects of data cleansing on load prediction algorithms

  • Hoverstad B.
  • Tidemann A.
  • Langseth H.

IEEE Symposium on Computational Intelligence Applications in Smart Grid, CIASG - 16/12/2013

10.1109/ciasg.2013.6611504

Cite count: 11 (Scopus)
  • SJR Categories: Artificial Intelligence; Computational Theory and Mathematics; Computer Networks and Communications; Computer Science Applications

Effects of scale on load prediction algorithms

  • Tidemann A.
  • Høverstad B.
  • Langseth H.
  • Öztürk P.

IET Conference Publications - 1/12/2013

10.1049/cp.2013.1116

Cite count: 7 (Scopus)
  • SJR Categories: Electrical and Electronic Engineering

Beating the bookie: A look at statistical models for prediction of football matches

  • Langseth H.

Frontiers in Artificial Intelligence and Applications - 1/12/2013

10.3233/978-1-61499-330-8-165

Cite count: 5 (Scopus)
  • SJR Quartile: Q3
  • CiteScore: 0.6 (2020)
  • SJR: 0.275 (2013
  • SNIP: 0.521 (2013
  • SJR Categories: Artificial Intelligence (Q3)
Open Access

Fast approximate inference in hybrid Bayesian networks using dynamic discretisation

  • Langseth H.
  • Marquez D.
  • Neil M.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 23/10/2013

10.1007/978-3-642-38637-4_23

Cite count: 2 (Scopus)
  • CiteScore: 1.8 (2020)
  • SJR: 0.36 (2013
  • SNIP: 0.775 (2013
Open Access

Mixtures of truncated basis functions

  • Langseth H.
  • Nielsen T.
  • Rumí R.
  • Salmerón A.

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING - 1/2/2012

10.1016/j.ijar.2011.10.004

Cite count: 56 (Web of Science) 55 (Scopus)
  • JCR Quartile: Q2 (2012)
  • SJR Quartile: Q1
  • JCR Impact Factor: 1.729 (2012)
  • Category normalized Impact: 1.763 (2012)
  • CiteScore: 7.1 (2020)
  • SJR: 1.494 (2012
  • SNIP: 2.132 (2012
  • JCR 5-year Impact Factor: 2.165
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Applied Mathematics (Q1); Artificial Intelligence (Q1); Software (Q1); Theoretical Computer Science (Q1)

This author has no patents.

This author has no reports or other types of publications.

Scopus: 18

Web of Science: 12

Scopus: 33

Web of Science: 13

Last data update: 5/18/24 9:32 AM
Next scheduled update: 5/25/24 3:00 AM