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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

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

Uncertainty bounds for a monotone multistate system

  • Langseth H.
  • Lindqvist B.

Probability in the Engineering and Informational Sciences - 1/12/1998

10.1017/s0269964800005179

Cite count: 10 (Scopus)
  • CiteScore: 1.7 (2020)

The SACSO methodology for troubleshooting complex systems

  • Jensen F.
  • Kjærulff U.
  • Kristiansen B.
  • Langseth H.
  • Skaanning C.
  • Vomlel J.
  • Vomlelová M.
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Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM - 1/9/2001

10.1017/s0890060401154065

Cite count: 55 (Scopus)
  • SJR Quartile: Q1
  • CiteScore: 2.9 (2020)
  • SJR: 0.365 (2001
  • SNIP: 0.885 (2001
  • SJR Categories: Industrial and Manufacturing Engineering (Q1); Artificial Intelligence (Q3)

Short-Term Load Forecasting With Seasonal Decomposition Using Evolution for Parameter Tuning

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

IEEE Transactions on Smart Grid - 1/7/2015

10.1109/tsg.2015.2395822

Cite count: 51 (Scopus)
  • SJR Quartile: Q1
  • JCR Impact Factor: 3.19 (2015)
  • CiteScore: 19.6 (2020)
  • SJR: 3.424 (2015
  • SNIP: 3.286 (2015
  • JCR 5-year Impact Factor: 5.104
  • JCR Categories: ENGINEERING, ELECTRICAL & ELECTRONIC
  • SJR Categories: Computer Science (miscellaneous) (Q1)
Open Access

Scaling up Bayesian variational inference using distributed computing clusters

  • Masegosa A.
  • Martinez A.
  • Langseth H.
  • Nielsen T.
  • Salmerón A.
  • Ramos-López D.
  • Madsen A.
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International Journal of Approximate Reasoning - 1/09/2017

10.1016/j.ijar.2017.06.010

Cite count: 9 (Web of Science) 10 (Scopus)
  • JCR Quartile: Q2 (2017)
  • SJR Quartile: Q1
  • JCR Impact Factor: 1.766 (2022)
  • Category normalized Impact: 0.343 (2017)
  • CiteScore: 7.1 (2020)
  • SJR: 0.866 (2017
  • SNIP: 1.746 (2017
  • JCR 5-year Impact Factor: 2.504
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Artificial Intelligence (Q1); Software (Q1); Theoretical Computer Science (Q1); Applied Mathematics (Q2)

Scalable learning of probabilistic latent models for collaborative filtering

  • Langseth H.
  • Nielsen T.

Decision Support Systems - 1/6/2015

10.1016/j.dss.2015.03.006

Cite count: 16 (Web of Science) 15 (Scopus)
  • SJR Quartile: Q1
  • JCR Impact Factor: 2.604 (2015)
  • CiteScore: 10.5 (2020)
  • SJR: 1.87 (2015
  • SNIP: 2.284 (2015
  • JCR 5-year Impact Factor: 3.271
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Arts and Humanities (miscellaneous) (Q1); Developmental and Educational Psychology (Q1); Information Systems (Q1); Information Systems and Management (Q1); Management Information Systems (Q1)
Open Access

Scalable importance sampling estimation of Gaussian mixture posteriors in Bayesian networks

  • Ramos-López D.
  • Masegosa A.
  • Salmerón A.
  • Rumí R.
  • Langseth H.
  • Nielsen T.
  • Madsen A.
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International Journal of Approximate Reasoning - 1/09/2018

10.1016/j.ijar.2018.06.004

Cite count: 9 (Web of Science) 4 (Scopus)
  • JCR Quartile: Q3 (2018)
  • SJR Quartile: Q2
  • JCR Impact Factor: 1.982 (2022)
  • Category normalized Impact: 0.402 (2018)
  • CiteScore: 7.1 (2020)
  • SJR: 0.606 (2018
  • SNIP: 1.453 (2018
  • JCR 5-year Impact Factor: 2.2
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Applied Mathematics (Q2); Artificial Intelligence (Q2); Software (Q2); Theoretical Computer Science (Q2)
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

Parameter learning in object-oriented Bayesian networks

  • Langseth H.
  • Bangsø O.

Annals of Mathematics and Artificial Intelligence - 1/12/2001

10.1023/a:1016769618900

Cite count: 27 (Scopus)
  • SJR Quartile: Q2
  • CiteScore: 2.5 (2020)
  • SJR: 0.747 (2001
  • SNIP: 1.542 (2001
  • SJR Categories: Applied Mathematics (Q2); 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)

Understanding and improving recurrent networks for human activity recognition by continuous attention

  • Zeng M.
  • Gao H.
  • Yu T.
  • Mengshoel O.
  • Langseth H.
  • Lane I.
  • Liu X.
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Proceedings - International Symposium on Wearable Computers, ISWC - 8/10/2018

10.1145/3267242.3267286

Cite count: 54 (Scopus)
  • SJR Categories: Computer Networks and Communications; Engineering (miscellaneous); Hardware and Architecture; Software

Towards a more expressive model for dynamic classification

  • Zhong S.
  • Martínez A.
  • Nielsen T.
  • Langseth H.

Proceedings of the 23rd International Florida Artificial Intelligence Research Society Conference, FLAIRS-23 - 19/10/2010

Cite count: 3 (Scopus)
  • SJR Categories: Artificial Intelligence; Control and Systems Engineering
Open Access

Scalable MAP inference in Bayesian networks based on a Map-Reduce approach

  • Ramos-L pez D.o.
  • Salmer n A.
  • Rum R.
  • Mart nez A.M.
  • Nielsen T.D.
  • Masegosa A.R.
  • Langseth H.
  • Madsen A.L.
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Proceedings of the Eighth International Conference on Probabilistic Graphical Models - 1/1/2016

Cite count:
  • JCR Impact Factor: 5 (2016)
  • CiteScore: 6.8 (2020)
  • SJR: 1.29 (2016
  • SNIP: 2.222 (2016
  • JCR 5-year Impact Factor: 7.649
  • JCR Categories: AUTOMATION & CONTROL SYSTEMS

Providing Previously Unseen Users Fair Recommendations Using Variational Autoencoders

  • Bjørnar Vassøy
  • Helge Langseth
  • Benjamin Kille

Proceedings of the 17th ACM Conference on Recommender Systems, RecSys 2023 - 14/09/2023

10.1145/3604915.3608842

Cite count:

Probability-based approach for predicting e-commerce consumer behaviour using sparse session data

  • Myklatun Ø.
  • Thorrud T.
  • Nguyen H.
  • Langseth H.
  • Kofod-Petersen A.

Proceedings of the International ACM Recommender Systems Challenge 2015 - 16/9/2015

10.1145/2813448.2813514

Cite count:
  • SJR Categories: Engineering (miscellaneous)

Prediction intervals: Split normal mixture from quality-driven deep ensembles

  • Salem T.S.
  • Langseth H.
  • Ramampiaro H.

Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence, UAI 2020 - 1/1/2020

Cite count: 1 (Scopus)
Open Access

Parameter learning in MTE networks using incomplete data

  • Fernández A.
  • Langseth H.
  • Nielsen T.
  • Salmerón A.

The Fifth European Workshop on Probabilistic Graphical Models, Helsinki, Finland, 12/09/2010 - 1/12/2010

Cite count: 4 (Scopus)
  • SJR Categories: Statistics and Probability
Open Access

Parameter estimation in mixtures of truncated exponentials

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

Proceedings of the Fourth European Workshop on Probabilistic Graphical Models - 1/12/2008

Cite count: 3 (Scopus)
  • SJR Categories: Statistics and Probability
Open Access

Parallelisation of the PC Algorithm

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

Advances in Artificial Intelligence - 1/1/2015

10.1007/978-3-319-24598-0_2

Cite count: 5 (Web of Science) 6 (Scopus)
  • Category normalized Impact: 0.64 (2015)
  • 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

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