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Langseth, Helge Autor

Parameter learning in object-oriented Bayesian networks

  • Langseth H.
  • Bangsø O.

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

10.1023/a:1016769618900

Número de citas: 27 (Scopus)
  • Cuartil SJR: Q2
  • CiteScore: 2,5 (2020)
  • SJR: 0,747 (2001)
  • SNIP: 1,542 (2001)
  • Categorías SJR: Applied Mathematics (Q2); Artificial Intelligence (Q2)

Effective hate-speech detection in Twitter data using recurrent neural networks

  • Pitsilis G.
  • Ramampiaro H.
  • Langseth H.

APPLIED INTELLIGENCE - 1/12/2018

10.1007/s10489-018-1242-y

Número de citas: 67 (Scopus)
  • Cuartil SJR: Q2
  • Factor Impacto JCR: 2,882 (2018)
  • CiteScore: 6,8 (2020)
  • SJR: 0,651 (2018)
  • SNIP: 1,585 (2018)
  • Impacto JCR a 5 años: 2,712
  • Categorías JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • Categorías SJR: Artificial Intelligence (Q2)

Simulating Vortex-Induced Vibrations in Sheared Current by Using an Empirical Time-Domain Model with Adaptive Parameters

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

Applied Ocean Research - 1/12/2024

10.1016/j.apor.2024.104284

Número de citas:
  • CiteScore: 8,7 (2023)
  • SJR: 1,184 (2023)
  • SNIP: 1,718 (2023)

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

Número de citas: 5 (Web of Science) 3 (Scopus)
  • Cuartil SJR: Q1
  • Factor Impacto JCR: 2,753 (2019)
  • CiteScore: 4,5 (2020)
  • SJR: 1,288 (2019)
  • SNIP: 2,113 (2019)
  • Impacto JCR a 5 años: 2,935
  • Categorías JCR: ENGINEERING, OCEAN
  • Categorías SJR: Ocean Engineering (Q1)

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

Número de citas: 55 (Scopus)
  • Cuartil SJR: Q1
  • CiteScore: 2,9 (2020)
  • SJR: 0,365 (2001)
  • SNIP: 0,885 (2001)
  • Categorías SJR: Industrial and Manufacturing Engineering (Q1); Artificial Intelligence (Q3)
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

Número de citas: 2 (Scopus)
  • CiteScore: 22 (2023)
  • SJR: 3,26 (2023)
  • SNIP: 5,068 (2023)
Open Access

Artificial intelligence and headache

  • Stubberud A.
  • Langseth H.
  • Nachev P.
  • Matharu M.S.
  • Tronvik E.

Cephalalgia - 1/8/2024

10.1177/03331024241268290

Número de citas:
  • CiteScore: 10,1 (2023)
  • SJR: 1,382 (2023)
  • SNIP: 1,413 (2023)
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 - 1/5/2024

10.1177/03331024241251488

Número de citas: 2 (Scopus)
  • CiteScore: 10,1 (2023)
  • SJR: 1,382 (2023)
  • SNIP: 1,413 (2023)

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

Número de citas: 16 (Web of Science) 15 (Scopus)
  • Cuartil SJR: Q1
  • Factor Impacto JCR: 2,604 (2015)
  • CiteScore: 10,5 (2020)
  • SJR: 1,87 (2015)
  • SNIP: 2,284 (2015)
  • Impacto JCR a 5 años: 3,271
  • Categorías JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • Categorías SJR: Arts and Humanities (miscellaneous) (Q1); Developmental and Educational Psychology (Q1); Information Systems (Q1); Information Systems and Management (Q1); Management Information Systems (Q1)
Open Access

Probabilistic Models with Deep Neural Networks

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

ENTROPY - 1/1/2021

10.3390/e23010117

Número de citas: 6 (Web of Science)
  • Cuartil JCR: Q2 (2021)
  • Factor Impacto JCR: 2,738 (2023)
  • Impacto Normalizado por Categoría: 0,1 (2021)
  • CiteScore: 4 (2020)
  • SJR: 0,468 (2020)
  • SNIP: 1,059 (2020)
  • Impacto JCR a 5 años: 2,642
  • Categorías JCR: PHYSICS, MULTIDISCIPLINARY

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

Número de citas:
  • Dialnet

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

  • Langseth H.

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

Número de citas: 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

Número de citas: 7 (Scopus)
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, Ecsqaru 2015 - 1/1/2015

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

Número de citas: 4 (Scopus)
  • CiteScore: 1,8 (2020)
  • SJR: 0,369 (2015)
  • SNIP: 0,708 (2015)

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

Número de citas: 2 (Scopus)
  • Categorías SJR: Computational Theory and Mathematics; Computer Networks and Communications; Software

Financial Data Analysis with PGMs using AMIDST

  • Cabanas R.
  • Martinez A.
  • Masegosa A.
  • Ramos-Lopez D.
  • Sameron A.
  • Nielsen T.
  • Langseth H.
  • Madsen A.
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2016 IEEE 16TH INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW) - 30/01/2016

10.1109/icdmw.2016.170

Número de citas: 4 (Web of Science) 4 (Scopus)
  • Impacto Normalizado por Categoría: 0,586 (2016)
  • Categorías SJR: Computer Science Applications; 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

Número de citas: 4 (Scopus)

Bayesian models of data streams with hierarchical power priors

  • Masegosa A.
  • Nielsen T.
  • Langseth H.
  • Ramos-López D.
  • Salmerón A.
  • Madsen A.

34th International Conference on Machine Learning, ICML 2017 - 1/1/2017

Número de citas: 2 (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

Número de citas: 25 (Scopus)
  • Categorías SJR: Ocean Engineering
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 (CAEPIA 2015) - 1/1/2015

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

Número de citas: 6 (Web of Science) 7 (Scopus)
  • Impacto Normalizado por Categoría: 0,767 (2015)
  • CiteScore: 1,8 (2020)
  • SJR: 0,369 (2015)
  • SNIP: 0,708 (2015)
Open Access

Parallelisation of the PC Algorithm

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

ADVANCES IN ARTIFICIAL INTELLIGENCE (CAEPIA 2015) - 1/1/2015

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

Número de citas: 7 (Web of Science) 6 (Scopus)
  • Impacto Normalizado por Categoría: 0,64 (2015)
  • CiteScore: 1,8 (2020)
  • SJR: 0,369 (2015)
  • SNIP: 0,708 (2015)
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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ADVANCES IN INTELLIGENT DATA ANALYSIS XIV - 1/1/2015

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

Número de citas: 13 (Web of Science) 14 (Scopus)
  • Factor Impacto JCR: 15,491 (2022)
  • Impacto Normalizado por Categoría: 1,609 (2015)
  • CiteScore: 1,8 (2020)
  • SJR: 0,369 (2015)
  • SNIP: 0,708 (2015)
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

Número de citas: 1 (Scopus)
  • CiteScore: 0,8 (2020)
  • SJR: 0,167 (2017)
  • SNIP: 0,346 (2017)
  • Categorías SJR: Computer Science (miscellaneous)
Open Access

Bayesian Exploration in Deep Reinforcement Learning

  • Killingberg L.
  • Langseth H.

CEUR Workshop Proceedings - 1/1/2023

Número de citas:
  • CiteScore: 1,1 (2022)
  • SJR: 0,202 (2022)
  • SNIP: 0,223 (2022)

Este autor no tiene patentes.

Open Access

A Divide and Conquer Approach for Solving Structural Causal Models

  • Bjøru, Anna Rodum
  • Cabañas De Paz, Rafael
  • Langseth, Helge
  • Salmerón Cerdán, Antonio

12th International Conference on Probabilistic Graphical Models (PGM'2024) - 2024

Scopus: 18

Web of Science: 12

Scopus: 33

Web of Science: 18

Última actualización de los datos: 20/11/24 2:40
Próxima recolección programada: 23/11/24 3:00