Langseth, Helge Author

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

Cite count: 74 (Web of Science) 75 (Scopus)

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

Cite count: 5 (Web of Science) 4 (Scopus)

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

Cite count: 18 (Scopus)

Bayesian networks in reliability

  • Langseth H.
  • Portinale L.

Reliability Engineering and System Safety - 1/1/2007

10.1016/j.ress.2005.11.037

Cite count: 436 (Scopus)

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

Cite count: 25 (Scopus)

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

Cite count: 31 (Web of Science) 15 (Scopus)
Open Access

MAP inference in dynamic hybrid Bayesian networks

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

PROGRESS IN ARTIFICIAL INTELLIGENCE - 27/6/2017

10.1007/s13748-017-0115-7

Cite count: 6 (Web of Science) 4 (Scopus)

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)

Latent Classification Models for Binary Data

  • Langseth H.
  • Nielsen T.

Pattern Recognition - 1/11/2009

10.1016/j.patcog.2009.05.002

Cite count: 8 (Web of Science) 8 (Scopus)
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: 9 (Web of Science) 2 (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

Cite count: 4 (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)

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)

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

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.
... View more Collapse

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

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

Cite count: 4 (Web of Science) 4 (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)
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

Cite count: 10 (Web of Science) 14 (Scopus)
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

Cite count: 3 (Web of Science) 2 (Scopus)

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

Cite count: 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

Cite count:
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.
... View more Collapse

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

Cite count:

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

Cite count: 11 (Scopus)
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

Cite count: 3 (Scopus)

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)

This author has no patents.

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

Last data update: 11/20/24 2:40 AM
Next scheduled update: 11/23/24 3:00 AM