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Langseth, Helge Autor

Inference in hybrid Bayesian networks

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

RELIABILITY ENGINEERING & SYSTEM SAFETY - 1/10/2009

10.1016/j.ress.2009.02.027

Número de citas: 74 (Web of Science) 75 (Scopus)
  • Cuartil JCR: Q1 (2009)
  • Cuartil SJR: Q1
  • Factor Impacto JCR: 1,908 (2009)
  • Impacto Normalizado por Categoría: 2,242 (2009)
  • CiteScore: 9,3 (2020)
  • SJR: 1,142 (2009)
  • SNIP: 2,571 (2009)
  • Impacto JCR a 5 años: 2,305
  • Categorías JCR: ENGINEERING, INDUSTRIAL
  • Categorías SJR: Applied Mathematics (Q1); Industrial and Manufacturing Engineering (Q1); Safety, Risk, Reliability and Quality (Q1)

A classification-based approach to monitoring the safety of dynamic systems

  • Zhong, Shengtong
  • Langseth, Helge
  • Nielsen, Thomas Dyhre

RELIABILITY ENGINEERING and SYSTEM SAFETY - 1/01/2014

10.1016/j.ress.2013.07.016

Número de citas: 5 (Web of Science) 4 (Scopus)
  • Cuartil SJR: Q1
  • Factor Impacto JCR: 2,41 (2014)
  • CiteScore: 9,3 (2020)
  • SJR: 1,419 (2014)
  • SNIP: 2,616 (2014)
  • Impacto JCR a 5 años: 2,693
  • Categorías JCR: OPERATIONS RESEARCH & MANAGEMENT SCIENCE
  • Categorías SJR: Applied Mathematics (Q1); Industrial and Manufacturing Engineering (Q1); Safety, Risk, Reliability and Quality (Q1)

Analysis of OREDA data for maintenance optimisation

  • Langseth H.
  • Haugen K.
  • Sandtorv H.

Reliability Engineering and System Safety - 1/1/1998

10.1016/s0951-8320(98)83003-2

Número de citas: 18 (Scopus)
  • CiteScore: 9,3 (2020)

Bayesian networks in reliability

  • Langseth H.
  • Portinale L.

Reliability Engineering and System Safety - 1/1/2007

10.1016/j.ress.2005.11.037

Número de citas: 436 (Scopus)
  • Cuartil SJR: Q1
  • CiteScore: 9,3 (2020)
  • SJR: 0,74 (2007)
  • SNIP: 2,203 (2007)
  • Categorías SJR: Industrial and Manufacturing Engineering (Q1); Safety, Risk, Reliability and Quality (Q1); Applied Mathematics (Q2)

Decision theoretic troubleshooting of coherent systems

  • Langseth H.
  • Jensen F.

Reliability Engineering and System Safety - 1/4/2003

10.1016/s0951-8320(02)00202-8

Número de citas: 25 (Scopus)
  • Cuartil SJR: Q1
  • CiteScore: 9,3 (2020)
  • SJR: 0,414 (2003)
  • SNIP: 1,307 (2003)
  • Categorías SJR: Industrial and Manufacturing Engineering (Q1); Safety, Risk, Reliability and Quality (Q2); Applied Mathematics (Q3)

Learning similarity measures from data

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

PROGRESS IN ARTIFICIAL INTELLIGENCE - 1/6/2020

10.1007/s13748-019-00201-2

Número de citas: 31 (Web of Science) 15 (Scopus)
  • Cuartil SJR: Q2
  • CiteScore: 3,4 (2020)
  • SJR: 0,322 (2020)
  • SNIP: 0,746 (2020)
  • Categorías SJR: Artificial Intelligence (Q2)
Open Access

MAP inference in dynamic hybrid Bayesian networks

  • Ramos-López D.
  • Masegosa A.
  • Martínez A.
  • Salmerón A.
  • Nielsen T.
  • Langseth H.
  • Madsen A.
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PROGRESS IN ARTIFICIAL INTELLIGENCE - 27/6/2017

10.1007/s13748-017-0115-7

Número de citas: 6 (Web of Science) 4 (Scopus)
  • Impacto Normalizado por Categoría: 0,228 (2017)
  • CiteScore: 3,4 (2020)
  • SNIP: 0,943 (2017)
  • Categorías SJR: Artificial Intelligence

Uncertainty bounds for a monotone multistate system

  • Langseth H.
  • Lindqvist B.

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

10.1017/s0269964800005179

Número de citas: 10 (Scopus)
  • CiteScore: 1,7 (2020)

Latent Classification Models for Binary Data

  • Langseth H.
  • Nielsen T.

Pattern Recognition - 1/11/2009

10.1016/j.patcog.2009.05.002

Número de citas: 8 (Web of Science) 8 (Scopus)
  • Cuartil SJR: Q1
  • Factor Impacto JCR: 2,554 (2009)
  • CiteScore: 15,7 (2020)
  • SJR: 1,163 (2009)
  • SNIP: 2,837 (2009)
  • Impacto JCR a 5 años: 3,453
  • Categorías JCR: ENGINEERING, ELECTRICAL & ELECTRONIC
  • Categorías SJR: Artificial Intelligence (Q1); Computer Vision and Pattern Recognition (Q1); Signal Processing (Q1); Software (Q1)
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

Número de citas: 9 (Web of Science) 2 (Scopus)
  • Cuartil JCR: Q1 (2020)
  • Factor Impacto JCR: 2,258 (2023)
  • Impacto Normalizado por Categoría: 1,811 (2020)
  • Impacto JCR a 5 años: 2,165
  • Categorías JCR: MATHEMATICS
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)

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)

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)

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

Dynamic Bayesian modeling for risk prediction in credit operations

  • Borchani H.
  • Martínez A.
  • Masegosa A.
  • Langseth H.
  • Nielsen T.
  • Salmerón A.
  • Fernández A.
  • Madsen A.
  • Sáez R.
... Ver más Contraer

THIRTEENTH SCANDINAVIAN CONFERENCE ON ARTIFICIAL INTELLIGENCE (SCAI 2015) - 1/1/2015

10.3233/978-1-61499-589-0-17

Número de citas: 4 (Web of Science) 4 (Scopus)
  • Cuartil SJR: Q3
  • Impacto Normalizado por Categoría: 0,286 (2015)
  • CiteScore: 0,6 (2020)
  • SJR: 0,238 (2015)
  • SNIP: 0,429 (2015)
  • Categorías SJR: Artificial Intelligence (Q3)
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

Número de citas: 4 (Scopus)
  • Categorías SJR: Statistics and Probability
Open Access

Maximum Likelihood Learning of Conditional MTE Distributions

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

SYMBOLIC AND QUANTITATIVE APPROACHES TO REASONING WITH UNCERTAINTY, PROCEEDINGS - 27/8/2009

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

Número de citas: 10 (Web of Science) 14 (Scopus)
  • Cuartil JCR: Q2 (2009)
  • Impacto Normalizado por Categoría: 1,409 (2009)
  • CiteScore: 1,8 (2020)
  • SJR: 0,302 (2009)
  • SNIP: 0,586 (2009)
Open Access

Learning Conditional Distributions Using Mixtures of Truncated Basis Functions

  • Pérez-Bernabé I.
  • Salmerón A.
  • Langseth H.

SYMBOLIC AND QUANTITATIVE APPROACHES TO REASONING WITH UNCERTAINTY, ECSQARU 2015 - 1/1/2015

10.1007/978-3-319-20807-7_36

Número de citas: 3 (Web of Science) 2 (Scopus)
  • Impacto Normalizado por Categoría: 0,293 (2015)
  • CiteScore: 1,8 (2020)
  • SJR: 0,369 (2015)
  • SNIP: 0,708 (2015)

Comparative study of event prediction in power grids using supervised machine learning methods

  • Hoiem K.W.
  • Santi V.
  • Torsater B.N.
  • Langseth H.
  • Andresen C.A.
  • Rosenlund G.H.

SEST 2020 - 3rd International Conference on Smart Energy Systems and Technologies - 1/9/2020

10.1109/sest48500.2020.9203025

Número de citas: 2 (Scopus)

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

Número de citas:
  • Categorías SJR: Engineering (miscellaneous)
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.
... Ver más Contraer

Proceedings of the Eighth International Conference on Probabilistic Graphical Models - 1/1/2016

Número de citas:
  • Factor Impacto JCR: 5 (2016)
  • CiteScore: 6,8 (2020)
  • SJR: 1,29 (2016)
  • SNIP: 2,222 (2016)
  • Impacto JCR a 5 años: 7,649
  • Categorías JCR: AUTOMATION & CONTROL SYSTEMS

Inference in hybrid Bayesian networks with mixtures of truncated basis functions

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

Proceedings of the 6th European Workshop on Probabilistic Graphical Models, PGM 2012 - 1/12/2012

Número de citas: 11 (Scopus)
  • Categorías SJR: Statistics and Probability
Open Access

Parameter estimation in mixtures of truncated exponentials

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

Proceedings of the 4th European Workshop on Probabilistic Graphical Models, PGM 2008 - 1/12/2008

Número de citas: 3 (Scopus)
  • Categorías SJR: Statistics and Probability

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

Número de citas: 1 (Scopus)

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