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Langseth, Helge Author

Open Access

A review of inference algorithms for hybrid Bayesian networks

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

JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH - 1/8/2018

10.1613/jair.1.11228

Cite count: 17 (Web of Science) 16 (Scopus)
  • JCR Quartile: Q3 (2018)
  • SJR Quartile: Q1
  • JCR Impact Factor: 1.82 (2022)
  • Category normalized Impact: 0.256 (2018)
  • CiteScore: 3.23 (2018)
  • SJR: 0.754 (2018
  • SNIP: 2.084 (2018
  • JCR 5-year Impact Factor: 2.448
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Artificial Intelligence (Q1)
Open Access

Fusion of domain knowledge with data for structural learning in object oriented domains

  • Langseth H.
  • Nielsen T.

Journal of Machine Learning Research - 1/4/2004

10.1162/153244304773633852

Cite count: 16 (Web of Science) 32 (Scopus)
  • SJR Quartile: Q1
  • CiteScore: 6.8 (2020)
  • SJR: 1.691 (2004
  • SNIP: 6.419 (2004
  • SJR Categories: Artificial Intelligence (Q1); Control and Systems Engineering (Q1); Software (Q1); Statistics and Probability (Q1)

Modelling of dependence between critical failure and preventive maintenance: The repair alert model

  • Lindqvist B.
  • Støve B.
  • Langseth H.

Journal of Statistical Planning and Inference - 1/5/2006

10.1016/j.jspi.2004.10.033

Cite count: 22 (Scopus)
  • SJR Quartile: Q2
  • CiteScore: 1.4 (2020)
  • SJR: 0.937 (2006
  • SNIP: 1.051 (2006
  • SJR Categories: Applied Mathematics (Q2); Statistics and Probability (Q2); Statistics, Probability and Uncertainty (Q2)

Competing risks for repairable systems: A data study

  • Langseth H.
  • Lindqvist B.

Journal of Statistical Planning and Inference - 1/5/2006

10.1016/j.jspi.2004.10.032

Cite count: 33 (Scopus)
  • SJR Quartile: Q2
  • CiteScore: 1.4 (2020)
  • SJR: 0.937 (2006
  • SNIP: 1.051 (2006
  • SJR Categories: Applied Mathematics (Q2); Statistics and Probability (Q2); Statistics, Probability and Uncertainty (Q2)

AMIDST: A Java toolbox for scalable probabilistic machine learning

  • Masegosa A.
  • Martínez A.
  • Ramos-López D.
  • Cabañas R.
  • Salmerón A.
  • Langseth H.
  • Nielsen T.
  • Madsen A.
... View more Collapse

Knowledge-Based Systems - 1/01/2019

10.1016/j.knosys.2018.09.019

Cite count: 7 (Web of Science) 7 (Scopus)
  • JCR Quartile: Q1 (2019)
  • SJR Quartile: Q1
  • JCR Impact Factor: 5.921 (2022)
  • Category normalized Impact: 0.374 (2019)
  • CiteScore: 11.3 (2020)
  • SJR: 1.754 (2019
  • SNIP: 2.828 (2019
  • JCR 5-year Impact Factor: 6.075
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Artificial Intelligence (Q1); Information Systems and Management (Q1); Management Information Systems (Q1); Software (Q1)

A parallel algorithm for Bayesian network structure learning from large data sets

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

KNOWLEDGE-BASED SYSTEMS - 1/2/2017

10.1016/j.knosys.2016.07.031

Cite count: 62 (Web of Science) 50 (Scopus)
  • JCR Quartile: Q1 (2017)
  • SJR Quartile: Q1
  • JCR Impact Factor: 4.396 (2022)
  • Category normalized Impact: 2.246 (2017)
  • CiteScore: 11.3 (2020)
  • SJR: 1.378 (2017
  • SNIP: 2.349 (2017
  • JCR 5-year Impact Factor: 4.514
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Artificial Intelligence (Q1); Information Systems and Management (Q1); Management Information Systems (Q1); Software (Q1)
Open Access

Maximum Likelihood Learning of Conditional MTE Distributions

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

Lecture Notes in Computer Science - 27/8/2009

10.1007/978-3-642-02906-6_22

Cite count: 9 (Web of Science) 14 (Scopus)
  • JCR Quartile: Q2 (2009)
  • Category normalized Impact: 1.409 (2009)
  • CiteScore: 1.8 (2020)
  • SJR: 0.302 (2009
  • SNIP: 0.586 (2009

Classification using Hierarchical Naïve Bayes models

  • Langseth H.
  • Nielsen T.

Machine Learning - 1/5/2006

10.1007/s10994-006-6136-2

Cite count: 47 (Web of Science) 62 (Scopus)
  • SJR Quartile: Q1
  • CiteScore: 6.1 (2020)
  • SJR: 1.8 (2006
  • SNIP: 4.144 (2006
  • SJR Categories: Artificial Intelligence (Q1); Software (Q1)

Latent classification models

  • Langseth H.
  • Nielsen T.

Machine Learning - 1/6/2005

10.1007/s10994-005-0472-5

Cite count: 10 (Web of Science) 13 (Scopus)
  • SJR Quartile: Q1
  • CiteScore: 6.1 (2020)
  • SJR: 2.604 (2005
  • SNIP: 5.656 (2005
  • SJR Categories: Artificial Intelligence (Q1); Software (Q1)

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

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

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)

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

Local-global-learning of naive Bayesian classifier

  • Zhong S.
  • Langseth H.

2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009 - 1/12/2009

10.1109/icicic.2009.254

Cite count: 2 (Scopus)
  • SJR Categories: Computational Theory and Mathematics; Computer Networks and Communications; Software

Forecasting intra-hour imbalances in electric power systems

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

33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019 - 1/1/2019

Cite count: 4 (Scopus)

Inter-session modeling for session-based recommendation

  • Ruocco M.
  • Skrede O.
  • Langseth H.

ACM International Conference Proceeding Series - 27/8/2017

10.1145/3125486.3125491

Cite count: 25 (Scopus)
  • SJR Categories: Ocean Engineering
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.
... View more Collapse

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

Bayesian Exploration in Deep Reinforcement Learning

  • Killingberg L.
  • Langseth H.

CEUR Workshop Proceedings - 1/1/2023

Cite count:
  • CiteScore: 1.1 (2022)
  • SJR: 0.202 (2022
  • SNIP: 0.223 (2022
Open Access

Data driven case base construction for prediction of success of marine operations

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

CEUR Workshop Proceedings - 1/1/2017

Cite count: 1 (Scopus)
  • CiteScore: 0.8 (2020)
  • SJR: 0.167 (2017
  • SNIP: 0.346 (2017
  • SJR Categories: Computer Science (miscellaneous)
Open Access

Parallel Filter-Based Feature Selection Based on Balanced Incomplete Block Designs

  • Salmerón A.
  • Madsen A.
  • Jensen F.
  • Langseth H.
  • Nielsen T.
  • Ramos-López D.
  • Martínez A.
  • Masegosa A.
... View more Collapse

ECAI 2016 - 1/1/2016

10.3233/978-1-61499-672-9-743

Cite count:
  • SJR Quartile: Q3
  • CiteScore: 0.6 (2020)
  • SJR: 0.202 (2016
  • SNIP: 0.451 (2016
  • SJR Categories: Artificial Intelligence (Q3)

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)

Extended abstract: Combining CBR and BN using metareasoning

  • Houeland T.
  • Bruland T.
  • Aamodt A.
  • Langseth H.

Frontiers in Artificial Intelligence and Applications - 1/1/2011

10.3233/978-1-60750-754-3-189

Cite count: 1 (Scopus)
  • SJR Quartile: Q3
  • CiteScore: 0.6 (2020)
  • SJR: 0.246 (2011
  • SNIP: 0.583 (2011
  • SJR Categories: Artificial Intelligence (Q3)

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