Langseth, Helge Author

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)

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

Cite count: 67 (Scopus)

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

Cite count:

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

Cite count: 5 (Web of Science) 3 (Scopus)

The SACSO methodology for troubleshooting complex systems

  • Jensen F.
  • Kjærulff U.
  • Kristiansen B.
  • Langseth H.
  • Skaanning C.
  • Vomlel J.
  • Vomlelová M.
... View more Collapse

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM - 1/9/2001

10.1017/s0890060401154065

Cite count: 55 (Scopus)
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

Cite count: 2 (Scopus)
Open Access

Artificial intelligence and headache

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

Cephalalgia - 1/8/2024

10.1177/03331024241268290

Cite count:
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.
... View more Collapse

Cephalalgia - 1/5/2024

10.1177/03331024241251488

Cite count: 2 (Scopus)

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)
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

Cite count: 6 (Web of Science)

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)
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)

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)

Financial Data Analysis with PGMs using AMIDST

  • Cabanas R.
  • Martinez A.
  • Masegosa A.
  • Ramos-Lopez D.
  • Sameron A.
  • Nielsen T.
  • Langseth H.
  • Madsen A.
... View more Collapse

2016 IEEE 16TH INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW) - 30/01/2016

10.1109/icdmw.2016.170

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

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)

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

Cite count: 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

Cite count: 25 (Scopus)
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 (CAEPIA 2015) - 1/1/2015

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

Cite count: 6 (Web of Science) 7 (Scopus)
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

Cite count: 7 (Web of Science) 6 (Scopus)
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.
... View more Collapse

ADVANCES IN INTELLIGENT DATA ANALYSIS XIV - 1/1/2015

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

Cite count: 13 (Web of Science) 14 (Scopus)
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)
Open Access

Bayesian Exploration in Deep Reinforcement Learning

  • Killingberg L.
  • Langseth H.

CEUR Workshop Proceedings - 1/1/2023

Cite count:

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