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Langseth, Helge Autor

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.
... Ver más Contraer

Cephalalgia - 1/5/2024

10.1177/03331024241251488

Número de citas: 2 (Scopus)
  • CiteScore: 10,1 (2023)
  • SJR: 1,382 (2023)
  • SNIP: 1,413 (2023)
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: 3 (Scopus)
  • CiteScore: 22 (2023)
  • SJR: 3,26 (2023)
  • SNIP: 5,068 (2023)

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

Número de citas: 3 (Scopus)
  • CiteScore: 8,7 (2023)
  • SJR: 1,117 (2023)
  • SNIP: 1,973 (2023)
Open Access

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)
Open Access

Deep Contextual Grid Triplet Network for Context-Aware Recommendation

  • Sofia Aftab
  • Heri Ramampiaro
  • Helge Langseth
  • Massimiliano Ruocco

IEEE ACCESS - 1/1/2023

10.1109/access.2023.3310470

Número de citas: 1 (Web of Science)
  • Factor Impacto JCR: 3,4 (2023)
  • Impacto JCR a 5 años: 3,7
  • Categorías JCR: ENGINEERING, ELECTRICAL & ELECTRONIC
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: 7 (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

Machine Learning in Financial Market Surveillance: A Survey

  • Tiwari S.
  • Ramampiaro H.
  • Langseth H.

IEEE Access - 1/1/2021

10.1109/access.2021.3130843

Número de citas:
  • Factor Impacto JCR: 3,476 (2021)
  • Impacto JCR a 5 años: 3,758
  • Categorías JCR: COMPUTER SCIENCE, INFORMATION SYSTEMS

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: 33 (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

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

Opt-in Transparent Fairness for Recommender Systems

  • Bjørnar Vassøy
  • Benjamin Kille
  • Helge Langseth

2025

10.1007/978-3-031-88708-6_23

  • ORCID

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
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)

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

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)

Providing Previously Unseen Users Fair Recommendations Using Variational Autoencoders

  • Bjørnar Vassøy
  • Helge Langseth
  • Benjamin Kille

PROCEEDINGS OF THE 17TH ACM CONFERENCE ON RECOMMENDER SYSTEMS, RECSYS 2023 - 14/09/2023

10.1145/3604915.3608842

Número de citas: 4 (Web of Science)

On Reporting Robust and Trustworthy Conclusions from Model Comparison Studies Involving Neural Networks and Randomness

  • Odd Erik Gundersen
  • Saeid Shamsaliei
  • Håkon Sletten Kjærnli
  • Helge Langseth

PROCEEDINGS OF THE 1ST ACM CONFERENCE ON REPRODUCIBILITY AND REPLICABILITY, REP'23 - 27/06/2023

10.1145/3589806.3600044

Número de citas: 3 (Web of Science)

Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches

  • Tiwari, Shweta
  • Bell, Gavin
  • Langseth, Helge
  • Ramampiaro, Heri
  • Rocha, AP
  • Steels, L
  • VandenHerik, J
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ICAART: PROCEEDINGS OF THE 14TH INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE - VOL 3 - 2022

10.5220/0010991800003116

Número de citas:

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)

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)

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)

Understanding and improving recurrent networks for human activity recognition by continuous attention

  • Zeng M.
  • Gao H.
  • Yu T.
  • Mengshoel O.
  • Langseth H.
  • Lane I.
  • Liu X.
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Proceedings - International Symposium on Wearable Computers, ISWC - 8/10/2018

10.1145/3267242.3267286

Número de citas: 54 (Scopus)
  • Categorías SJR: Computer Networks and Communications; Engineering (miscellaneous); Hardware and Architecture; Software

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

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)

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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: 12/04/25 9:51
Próxima recolección programada: 19/04/25 3:00