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  1. Ansatte

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English

Helge Langseth

Last ned pressefoto
Last ned pressefoto
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Helge Langseth

Professor
Institutt for datateknologi og informatikk
Fakultet for informasjonsteknologi og elektroteknikk

helge.langseth@ntnu.no
312 IT-bygget Gløshaugen, Trondheim
Google Scholar Norwegian Open AI Lab
Om Publikasjoner Undervisning Formidling

Om

Forskningsområde: Kunstig Intelligens

Jeg jobber med systemer som skal hjelpe mennesker med å ta vanskelige beslutninger, spesielt i situasjoner der beslutningene skal tas basert på delvis manglende eller usikker informasjon. Konkret er jeg interessert i 

  • Probabilistiske grafiske modeller, spesielt Bayesianske nett
  • Beslutningsstøtte-systemer
  • Bayesianske metoder
  • Maskinlæring
  • Kunstig intelligens (AI)

Forskningsgruppe:  Intelligente systemer

Personlig hjemmeside: www.idi.ntnu.no/~helgel/

 

Kompetanseord

  • Kunstig intelligens
  • Maskinlæring

Publikasjoner

  • Kronologisk
  • Etter kategori
  • Alle publikasjoner i Nasjonalt vitenarkiv (NVA)

2026

  • Bjøru, Anna Rodum; Langseth, Helge; Strumke, Inga; Bach, Kerstin. (2026) Causal Post-hoc Explainable AI. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling
  • Bjøru, Anna Rodum; Lysnæs-Larsen, Jacob; Jørgensen, Oskar; Strumke, Inga; Langseth, Helge. (2026) A framework for causal concept-based model explanations. Frontiers in Artificial Intelligence
    Vitenskapelig artikkel
  • Vassøy, Bjørnar; Langseth, Helge; Kille, Benjamin Uwe; Vinterbo, Staal Amund. (2026) Consumer-side Fairness in Recommender Systems. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling

2025

  • Bekkemoen, Yanzhe; Langseth, Helge. (2025) Interpretable Deep Reinforcement Learning Via Concept-Based Policy Distillation. Machine Learning
    Vitenskapelig artikkel
  • Aftab, Sofia; Ramampiaro, Heri; Langseth, Helge; Ruocco, Massimiliano. (2025) Improving Top-N Recommendations: Leveraging Pair-Wise Deep Learning Methods and Evaluation Metrics Contextual modeling, Pair-wise loss functions and Metric enhancement. NTNU Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling
  • Bjøru, Anna Rodum; Cabañas, Rafael; Langseth, Helge; Salmeron, Antonio. (2025) Divide and conquer for causal computation. International Journal of Approximate Reasoning
    Vitenskapelig artikkel
  • Danelakis, Antonios; Kumelj, Tjasa; Winsvold, Bendik S.; Bjørk, Marte Helene; Nachev, Parashkev; Matharu, Manjit; Giles, Dominic; IHGC, Int. Headache Genetic Cons.; Tronvik, Erling Andreas; Langseth, Helge. (2025) Diagnosing migraine from genome-wide genotype data: a machine learning analysis. Brain
    Vitenskapelig artikkel
  • Vassøy, Bjørnar; Kille, Benjamin Uwe; Langseth, Helge. (2025) Opt-in Transparent Fairness for Recommender Systems. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Langseth, Helge; Bekkemoen, Yanzhe. (2025) Explainable Reinforcement Learning (XRL): Simplifying Agent Behavior. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling
  • Herland, Sverre; Bach, Kerstin; Misimi, Ekrem; Langseth, Helge. (2025) Reinforcement Learning for Robotic Control and Manipulation in Ocean Space Applications. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling

2024

  • Danelakis, Antonios; Langseth, Helge; Nachev, Parashkev; Nelson, Amy; Bjørk, Marte-Helene; Matharu, Manjit Singh; Tronvik, Erling Andreas; May, Arne; Stubberud, Anker. (2024) What predicts citation counts and translational impact in headache research? A machine learning analysis. Cephalalgia
    Vitenskapelig artikkel
  • Stubberud, Anker; Langseth, Helge; Nachev, Parashkev; Matharu, Manjit S.; Tronvik, Erling Andreas. (2024) Artificial intelligence and headache. Cephalalgia
    Vitenskapelig oversiktsartikkel
  • Bjøru, Anna Rodum; Cabañas, Rafael; Langseth, Helge; Salmerón, Antonio. (2024) A Divide and Conquer Approach for Solving Structural Causal Models. Proceedings of Machine Learning Research (PMLR)
    Vitenskapelig artikkel
  • Andersen, Martin Lieberkind; Sævik, Svein; Wu, Jie; Leira, Bernt Johan; Langseth, Helge. (2024) Simulating Vortex-Induced Vibrations in Sheared Current by Using an Empirical Time-Domain Model with Adaptive Parameters. Applied Ocean Research
    Vitenskapelig artikkel
  • Andersen, Martin Lieberkind; Sævik, Svein; Wu, Jie; Leira, Bernt Johan; Langseth, Helge. (2024) Applying Bayesian optimization to predict parameters in a time-domain model for cross-flow vortex-induced vibrations. Marine Structures
    Vitenskapelig artikkel
  • Vassøy, Bjørnar; Langseth, Helge. (2024) Consumer-side fairness in recommender systems: a systematic survey of methods and evaluation. Artificial Intelligence Review
    Vitenskapelig oversiktsartikkel
  • Bekkemoen, Yanzhe; Langseth, Helge. (2024) ASAP: Attention-Based State Space Abstraction for Policy Summarization. Proceedings of Machine Learning Research (PMLR)
    Vitenskapelig artikkel
  • Flogard, Eirik Lund; Mengshoel, Ole Jakob; Langseth, Helge; Ramampiaro, Heri; Bach, Kerstin. (2024) Improving Labour Inspection Efficiency via Machine Learning. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling

2023

  • Killingberg, Ludvig; Langseth, Helge. (2023) The Multiquadric Kernel for Moment-Matching Distributional Reinforcement Learning. Transactions on Machine Learning Research (TMLR)
    Vitenskapelig artikkel
  • Vassøy, Bjørnar; Langseth, Helge; Kille, Benjamin Uwe. (2023) Providing Previously Unseen Users Fair Recommendations Using Variational Autoencoders.
    Vitenskapelig kapittel
  • Gundersen, Odd Erik; Shamsaliei, Saeid; Kjærnli, Håkon Slåtten; Langseth, Helge. (2023) On Reporting Robust and Trustworthy Conclusions from Model Comparison Studies Involving Neural Networks and Randomness.
    Vitenskapelig kapittel
  • Aftab, Sofia; Ramampiaro, Heri; Langseth, Helge; Ruocco, Massimiliano. (2023) Deep Contextual Grid Triplet Network for Context-Aware Recommendation. IEEE Access
    Vitenskapelig artikkel
  • Killingberg, Ludvig; Langseth, Helge. (2023) Bayesian Exploration in Deep Reinforcement Learning. CEUR Workshop Proceedings
    Vitenskapelig artikkel
  • Myhre, Henrik; Matsen, Erik; Langseth, Helge. (2023) Making Sense of Tabular Neural Networks: Interpretability using Concept Detection. NTNU
    Masteroppgave
  • Hanssen, Jørgen; Langseth, Helge. (2023) Expanding Our Knowledge of Maritime Trade with AIS and Explainable AI Systems. Norges teknisk-naturvitenskapelige universitet
    Masteroppgave
  • Baumgartner, David; Langseth, Helge; Ramampiaro, Heri; Engø-Monsen, Kenth. (2023) mTADS: Multivariate Time Series Anomaly Detection Benchmark Suites.
    Vitenskapelig kapittel

2022

  • Salmeron, Antonio; Langseth, Helge; Masegosa, Andres; Nielsen, Thomas D.. (2022) A Reparameterization of Mixtures of Truncated Basis Functions and its Applications. Proceedings of Machine Learning Research (PMLR)
    Vitenskapelig artikkel
  • Tiwari, Shweta; Bell, Gavin; Langseth, Helge; Ramampiaro, Heri. (2022) Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches. Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART)
    Vitenskapelig artikkel
  • Andersen, Martin Lieberkind; Sævik, Svein; Leira, Bernt Johan; Wu, Jie; Langseth, Helge; Passano, Elizabeth Anne; Lie, Halvor; Yin, Decao. (2022) Estimation of VIV-parameters based on Response Measurements and Bayesian Machine Learning Algorithms.
    Vitenskapelig kapittel
  • Langseth, Helge; Høijord, Espen Hansen. (2022) Explainable AI (XAI) for grid loss forecasting. Norges teknisk-naturvitenskapelige universitet
    Masteroppgave

2021

  • Bekkemoen, Yanzhe; Langseth, Helge. (2021) Correcting Classification: A Bayesian Framework Using Explanation Feedback to Improve Classification Abilities. Norges teknisk-naturvitenskapelige universitet
    Masteroppgave
  • Masegosa, Andres; Cabañas, Rafael; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio. (2021) Probabilistic Models with Deep Neural Networks. Entropy
    Vitenskapelig artikkel
  • Mathisen, Bjørn Magnus; Aamodt, Agnar; Bach, Kerstin; Langseth, Helge. (2021) Using similarity learning to enable decision support in aquaculture. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling
  • Kvamme, Johannes; Larsen, Pål-Edward; Langseth, Helge. (2021) Achieving Trustable Explanations Through Multi-Task Learning Neural Networks. Norges teknisk-naturvitenskapelige universitet
    Masteroppgave
  • da Silva, Eliezer de Souza; Langseth, Helge; Ramampiaro, Heri. (2021) Factorization models with relational and contextual information: Probabilistic factorization, Point processes and neural sequential models. Norwegian University of Science and Technology
    Doktoravhandling
  • Tiwari, Shweta; Ramampiaro, Heri; Langseth, Helge. (2021) Machine Learning in Financial Market Surveillance: A Survey. IEEE Access
    Vitenskapelig oversiktsartikkel

2020

  • Høiem, Kristian Wang; Santi, Vemund Mehl; Torsæter, Bendik Nybakk; Langseth, Helge; Andresen, Christian Andre; Rosenlund, Gjert Hovland. (2020) Comparative Study of Event Prediction in Power Grids using Supervised Machine Learning Methods.
    Vitenskapelig kapittel
  • Masegosa, Andres; Ramos-López, Dario; Salmeron, Antonio; Langseth, Helge; Nielsen, Thomas D.. (2020) Variational Inference over Nonstationary Data Streams for Exponential Family Models. Mathematics
    Vitenskapelig artikkel
  • Masegosa, Andres; Martinez, Ana M.; Ramos-López, Dario; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio. (2020) Analyzing concept drift: A case study in the financial sector. Intelligent Data Analysis
    Vitenskapelig artikkel
  • Saleh Salem, Tárik; Langseth, Helge; Ramampiaro, Heri. (2020) Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles. Proceedings of Machine Learning Research (PMLR)
    Vitenskapelig artikkel

2019

  • Ramampiaro, Heri; Langseth, Helge; Almenningen, Thomas; Schistad, Herman; Havig, Martin Christian; Nguyen, Hai Thanh. (2019) New Ideas in Ranking for Personalized Fashion Recommender Systems.
    Vitenskapelig kapittel
  • Saleh Salem, Tárik; Kathuria, Karan; Ramampiaro, Heri; Langseth, Helge. (2019) Forecasting Intra-Hour Imbalances in Electric Power Systems. Proceedings of the AAAI Conference on Artificial Intelligence
    Vitenskapelig artikkel
  • Mathisen, Bjørn Magnus; Aamodt, Agnar; Langseth, Helge; Bach, Kerstin. (2019) Learning similarity measures from data. Progress in Artificial Intelligence
    Vitenskapelig artikkel
  • Swider, Anna; Langseth, Helge; Pedersen, Eilif. (2019) Application of data-driven models in the analysis of marine power systems. Applied Ocean Research
    Vitenskapelig artikkel
  • Masegosa, Andres; Martinez, Ana M.; Ramos-López, Dario; Cabañas, Rafael; Salmeron, Antonio; Langseth, Helge; Nielsen, Thomas D.. (2019) AMIDST: A Java toolbox for scalable probabilistic machine learning. Knowledge-Based Systems
    Vitenskapelig artikkel

2018

  • Masegosa, Andres; Martinez, Ana M.; Ramos-López, Dario; Cabañas, Rafael; Salmerón, Antonio; Langseth, Helge; Nielsen, Thomas D.; Madsen, Anders L.. (2018) AMIDST: A Java toolbox for scalable probabilistic machine learning. Knowledge-Based Systems
    Vitenskapelig artikkel
  • Salmeron, Antonio; Rumi, Rafael; Langseth, Helge; Nielsen, Thomas D.; Madsen, Anders L.. (2018) A Review of Inference Algorithms for Hybrid Bayesian Networks. The journal of artificial intelligence research
    Vitenskapelig oversiktsartikkel
  • Ramos-López, Dario; Masegosa, Andres R.; Salmerón, Antonio; Rumi, Rafael; Langseth, Helge; Nielsen, Thomas D.; Madsen, Anders L.. (2018) Scalable importance sampling estimation of Gaussian mixture posteriors in Bayesian networks. International Journal of Approximate Reasoning
    Vitenskapelig artikkel
  • Agarwal, Basant; Ramampiaro, Heri; Langseth, Helge; Ruocco, Massimiliano. (2018) A deep network model for paraphrase detection in short text messages. Information Processing & Management
    Vitenskapelig artikkel
  • Pitsilis, Georgios; Ramampiaro, Heri; Langseth, Helge. (2018) Effective hate-speech detection in Twitter data using recurrent neural networks. Applied Intelligence - The International Journal of Research on Intelligent Systems for Real Life Complex Problems
    Vitenskapelig artikkel
  • Zeng, Ming; Gao, Haoxiang; Yu, Tong; Mengshoel, Ole Jakob; Langseth, Helge; Lane, Ian; Liu, Xiaobing. (2018) Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention.
    Vitenskapelig kapittel

2017

  • Masegosa, Andres R.; Nielsen, Thomas D.; Langseth, Helge; Ramos-López, Dario; Salmeron, Antonio; Madsen, Anders L.. (2017) Bayesian Models of Data Streams with Hierarchical Power Priors. JMLR Workshop and Conference Proceedings
    Vitenskapelig artikkel
  • Cabañas, Rafael; Martínez, Ana M.; Masegosa, Andres R.; Ramos-López, Darío; Salmerón, Antonio; Nielsen, Thomas D.; Langseth, Helge; Madsen, Anders L.. (2017) Financial data analysis with PGMs using AMIDST. IEEE International Conference on Data Mining Workshops, ICDMW
    Vitenskapelig artikkel
  • da Silva, Eliezer de Souza; Langseth, Helge; Ramampiaro, Heri. (2017) Content-Based Social Recommendation with Poisson Matrix Factorization. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Ramos-López, Dario; Masegosa, Andres R.; Martinez, Ana M.; Salmeron, Antonio; Nielsen, Thomas D.; Langseth, Helge; Madsen, Anders L.. (2017) MAP inference in dynamic hybrid Bayesian networks. Progress in Artificial Intelligence
    Vitenskapelig artikkel
  • Madsen, Anders L.; Jensen, Frank; Salmeron, Antonio; Langseth, Helge; Nielsen, Thomas D.. (2017) A parallel algorithm for Bayesian network structure learning from large data sets. Knowledge-Based Systems
    Vitenskapelig artikkel
  • Mathisen, Bjørn Magnus; Aamodt, Agnar; Langseth, Helge. (2017) Data driven case base construction for prediction of success of marine operations. CEUR Workshop Proceedings
    Vitenskapelig artikkel
  • Ruocco, Massimiliano; Skrede, Ole Steinar Lillestøl; Langseth, Helge. (2017) Inter-Session Modeling for Session-Based Recommendation. Association for Computing Machinery (ACM)
    Antologi
  • Masegosa, Andres R.; Martinez, Ana M.; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio; Ramos-López, Dario; Madsen, Anders L.. (2017) Scaling up Bayesian variational inference using distributed computing clusters. International Journal of Approximate Reasoning
    Vitenskapelig artikkel

2016

  • Ramos-Lopez, Dario; Salmeron, Antonio; Rumi, Rafel; Martinez, Ana M.; Nielsen, Thomas D.; Masegosa Arredondo, Andres Ramon; Langseth, Helge; Madsen, Anders L.. (2016) Scalable MAP inference in Bayesian networks based on a Map-Reduce approach. Journal of machine learning research
    Vitenskapelig artikkel
  • Ramos-López, Dario; Salmeron, Antonio; Rumi, Rafael; Martinez, Ana M.; Nielsen, Thomas D.; Masegosa, Andres R.; Langseth, Helge; Madsen, Anders L.. (2016) Scalable MAP inference in Bayesian networks based on a Map-Reduce approach. Journal of machine learning research
    Vitenskapelig artikkel
  • Masegosa, Andres R.; Martinez, Ana M.; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio; Ramos-López, Dario; Madsen, Anders L.. (2016) d-VMP: Distributed Variational Message Passing. Journal of machine learning research
    Vitenskapelig artikkel
  • Salmerón, Antonio; Madsen, Anders L.; Jensen, Frank; Langseth, Helge; Nielsen, Thomas D.; Ramos-López, Dario; Martínez, Ana M.; Masegosa, Andres R.. (2016) Parallel filter-based feature selection based on balanced incomplete block designs. Frontiers in Artificial Intelligence and Applications
    Vitenskapelig artikkel

2015

  • Myklatun, Øyvind Herstad; Thorrud, Thorstein Kaldahl; Nguyen, Hai Thanh; Langseth, Helge; Kofod-Petersen, Anders. (2015) Probability-based Approach for Predicting E-commerce Consumer Behaviour Using Sparse Session Data.
    Vitenskapelig kapittel
  • Salmeron, Antonio; Ramoz-López, Darío; Borchani, Hanen; Martinez, Ana M.; Masegosa, Andres; Fernandez, Antonio; Langseth, Helge; Madsen, Anders L.; Nielsen, Thomas D.. (2015) Parallel importance sampling in conditional linear gaussian networks. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Borchani, Hanen; Martinez, Ana M.; Masegosa, Andres; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio; Fernandez, Antonio; Madsen, Anders L.; Sáez, Ramón. (2015) Modeling concept drift: A probabilistic graphical model based approach. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Madsen, Anders L.; Jensen, Frank; Salmeron, Antonio; Langseth, Helge; Nielsen, Thomas D.. (2015) Parallelization of the PC Algorithm. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Borchani, Hanen; Martinez, Ana M.; Masegosa, Andres; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio; Fernández, Antonio; Madsen, Anders L.; Sáez, Ramón. (2015) Dynamic Bayesian modeling for risk prediction in credit operations. Frontiers in Artificial Intelligence and Applications
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.. (2015) Scalable learning of probabilistic latent models for collaborative filtering. Decision Support Systems
    Vitenskapelig artikkel
  • Salmeron, Antonio; Rumi, Rafael; Langseth, Helge; Madsen, Anders L.; Nielsen, Thomas D.. (2015) MPE inference in Conditional Linear Gaussian Networks. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Høverstad, Boye Annfelt; Tidemann, Axel; Langseth, Helge; Øzturk, Pinar. (2015) Short-Term Load Forecasting With Seasonal Decomposition Using Evolution for Parameter Tuning. IEEE Transactions on Smart Grid
    Vitenskapelig artikkel
  • Pérez-Bernabé, Inmaculada; Salmeron, Antonio; Langseth, Helge. (2015) Learning conditional distributions using mixtures of truncated basis functions. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel

2014

  • Nielsen, Thomas D.; Hovda, Sigve; Fernandez, Antonio; Langseth, Helge; Madsen, Anders L.; Masegosa, Andres; Salmeron, Antonio. (2014) Requirement Engineering for a Small Project with Pre-Specified Scope. NIKT: Norsk IKT-konferanse for forskning og utdanning
    Vitenskapelig artikkel
  • Madsen, Anders L.; Jensen, Frank; Salmeron, Antonio; Karlsen, Martin; Langseth, Helge; Nielsen, Thomas D.. (2014) A New Method for Vertical Parallelisation of TAN Learning Based on Balanced Incomplete Block Designs.
    Vitenskapelig kapittel
  • Zhong, Shengtong; Langseth, Helge; Nielsen, Thomas D.. (2014) A classification-based approach to monitoring the safety of dynamic systems. Reliability Engineering & System Safety
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.; Pérez-Bernabé, Inmaculada; Salmeron, Antonio. (2014) Learning mixtures of truncated basis functions from data. International Journal of Approximate Reasoning
    Vitenskapelig artikkel
  • Nguyen, Hai Thanh; Almenningen, Thomas; Havig, Martin; Schistad, Herman; Kofod-Petersen, Anders; Langseth, Helge; Ramampiaro, Heri. (2014) Learning to Rank for Personalized Fashion Recommender Systems via Implicit Feedback. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel

2013

  • Høverstad, Boye Annfelt; Tidemann, Axel; Langseth, Helge. (2013) Effects of data cleansing on load prediction algorithms.
    Vitenskapelig kapittel
  • Tidemann, Axel; Høverstad, Boye Annfelt; Langseth, Helge; Øzturk, Pinar. (2013) Effects of scale on load prediction algorithms.
    Vitenskapelig kapittel
  • Langseth, Helge; Marquez, David; Neil, Martin. (2013) Fast approximate inference in hybrid Bayesian networks using dynamic discretisation. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Langseth, Helge. (2013) Beating the bookie: A look at statistical models for prediction of football matches.
    Vitenskapelig kapittel

2012

  • Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio. (2012) Learning Mixtures of Truncated Basis Functions from Data.
    Vitenskapelig kapittel
  • Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2012) Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions.
    Vitenskapelig kapittel
  • Langseth, Helge; Nielsen, Thomas D.. (2012) A latent model for collaborative filtering. International Journal of Approximate Reasoning
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2012) Mixtures of truncated basis functions. International Journal of Approximate Reasoning
    Vitenskapelig artikkel

2011

  • Lillegraven, Terje N.; Wolden, Arnt C.; Kofod-Petersen, Anders; Langseth, Helge. (2011) A design for a tourist CF system. Frontiers in Artificial Intelligence and Applications
    Konferanseabstract
  • Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2011) A hybrid CBR and BN architecture refined through data analysis.
    Vitenskapelig kapittel
  • Kofod-Petersen, Anders; Heintz, Fredrik; Langseth, Helge. (2011) Eleventh Scandinavian Conference on Artificial Intelligence -- SCAI 2011. IOS Press
    Antologi
  • Kofod-Petersen, Anders; Heintz, Fredrik; Langseth, Helge. (2011) Foreword.
    Innledning i antologi
  • Houeland, Tor Gunnar Høst; Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2011) Combining CBR and BN using metareasoning. Frontiers in Artificial Intelligence and Applications
    Vitenskapelig artikkel

2010

  • Zhong, Shengtong; Martinez, Ana M.; Nielsen, Thomas D.; Langseth, Helge. (2010) Towards a More Expressive Model for Dynamic Classification.
    Vitenskapelig kapittel
  • Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2010) Architectures integrating case-based reasoning and Bayesian networks for clinical decision support.
    Vitenskapelig kapittel
  • Kofod-Petersen, Anders; Langseth, Helge; Aamodt, Agnar. (2010) Explanations in Bayesian networks using provenance through case-based reasoning.
    Vitenskapelig kapittel
  • Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2010) Architectures Integrating Case-Based Reasoning and Bayesian Networks for Clinical Decision Support. IFIP Advances in Information and Communication Technology
    Vitenskapelig artikkel
  • Fernandez, Antonio; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio. (2010) Parameter learning in MTE networks using incomplete data.
    Vitenskapelig kapittel
  • Kofod-Petersen, Anders; Langseth, Helge. (2010) Tourist Without a Cause.
    Vitenskapelig kapittel
  • Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2010) Parameter Estimation and Model Selection for Mixtures of Truncated Exponentials. International Journal of Approximate Reasoning
    Vitenskapelig artikkel

2009

  • Langseth, Helge; Nielsen, Thomas D.. (2009) A latent model for collaborative filtering. Aalborg Universitetsforlag
    Forskningsrapport
  • Kofod-Petersen, Anders; Langseth, Helge; Gundersen, Odd Erik. (2009) Preface.
    Innledning i antologi
  • Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2009) Maximum Likelihood Learning of Conditional MTE Distributions. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2009) Inference in Hybrid Bayesian Networks. Reliability Engineering & System Safety
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.. (2009) Latent Classification Models for Binary Data. Pattern Recognition
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2009) Maximum Likelihood Learning of Conditional MTE Distributions.
    Vitenskapelig kapittel
  • Kofod-Petersen, Anders; Langseth, Helge; Gundersen, Odd Erik. (2009) Proceedings of the First Norwegian Artificial Intelligence Symposium. Tapir Akademisk Forlag
    Antologi
  • Kofod-Pedersen, Anders; Langseth, Helge; Gundersen, Odd Erik. (2009) Proceedings of the First Norwegian Artificial Intelligence Symposium. Tapir Akademisk Forlag
    Antologi
  • Zhong, Shengtong; Langseth, Helge. (2009) Local-Global-Learning of Naive Bayesian Classifier.
    Vitenskapelig kapittel
  • Langseth, Helge. (2009) Bayesian Networks for Collaborative Filtering.
    Vitenskapelig kapittel
  • Kofod-Petersen, Anders; Langseth, Helge; Gundersen, Odd Erik. (2009) Proceedings of the first Norwegian Artificial Intelligence Symposium. Tapir Akademisk Forlag
    Antologi

2008

  • Langseth, Helge; Jensen, Finn V.. (2008) Bayesian Networks and Decision Graphs in Reliability.
    Vitenskapelig kapittel
  • Langseth, Helge. (2008) Bayesian networks in Reliability: The Good, The Bad, and The Ugly.
    Vitenskapelig kapittel

2007

  • Langseth, Helge; Portinale, Luigi. (2007) Applications of Bayesian Networks in Reliability Analysis.
    Vitenskapelig kapittel
  • Langseth, Helge; Portinale, Luigi. (2007) Bayesian Networks in Reliability. Reliability Engineering & System Safety
    Vitenskapelig artikkel
  • Langseth, Helge; Cojazzi, Giacomo G.M.. (2007) Reliability of Safety-Critical Systems: Proceedings of the 30th ESReDA Seminar Hosted by SINTEF, Trondheim, Norway June 7-8, 2006. Office for Official publications of the European communities
    Antologi

2006

  • Lindqvist, Bo Henry; Støve, Bård; Langseth, Helge. (2006) Modelling of dependence between critical failure and preventive maintenance: The repair alert model. Journal of Statistical Planning and Inference
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.. (2006) Classification using Hierarchical Naïve Bayes models. Machine Learning
    Vitenskapelig artikkel
  • Langseth, Helge; Lindqvist, Bo Henry. (2006) Competing risks for repairable systems: A data study. Journal of Statistical Planning and Inference
    Vitenskapelig artikkel
  • Vatn, Jørn; Langseth, Helge. (2006) Estimation of Weibull parameters when the i.i.d. assumption does not hold.
    Vitenskapelig kapittel
  • Lindqvist, Bo; Støve, Bård; Langseth, Helge. (2006) Modelling of dependence between critical failure and preventive maintenance: The repair alert model. Journal of Statistical Planning and Inference
    Vitenskapelig artikkel

2005

  • Lindqvist, Bo Henry; Langseth, Helge. (2005) Statistical modelling and inference for component failure times under preventive maintenance and independent censoring.
    Vitenskapelig kapittel
  • Hokstad, Per; Langseth, Helge; Lindqvist, Bo Henry; Vatn, Jørn. (2005) Failure modeling and maintenance optimization for a railway line. International Journal of Performability Engineering
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.. (2005) Latent classification models. Machine Learning
    Vitenskapelig artikkel

2004

  • Bjørkvoll, Thor; Langseth, Helge. (2004) The Prioritization of Risk Reducing Measures in View of Uncertain Cost/Benefits.
    Vitenskapelig kapittel

2003

  • Langseth, Helge; Nielsen, Thomas D.. (2003) Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains. Journal of machine learning research
    Vitenskapelig artikkel
  • Langseth, Helge; Lindqvist, Bo Henry. (2003) A maintenance model for components exposed to several failure mechanisms and imperfect repair.
    Vitenskapelig kapittel
  • Langseth, Helge; Jensen, Finn V.. (2003) Decision Theoretic Troubleshooting of Coherent Systems. Reliability Engineering & System Safety
    Vitenskapelig artikkel

2002

  • Langseth, Helge. (2002) Bayesian networks with applications in reliability analysis. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling

2001

  • Jensen, Finn V.; Kjærulff, Uffe; Langseth, Helge; Scaanning, Claus; Vomlelova, Marta; Vomlel, Jiri. (2001) The SACSO methodology for troubleshooting complex systems. Artificial intelligence for engineering design, analysis and manufacturing
    Vitenskapelig artikkel
  • Langseth, Helge; Bangsø, Olav. (2001) Parameter Learning in Object Oriented Bayesian Networks. Annals of Mathematics and Artificial Intelligence
    Vitenskapelig artikkel

1999

  • Langseth, Helge; Aamodt, Agnar; Winnem, Ole Martin. (1999) Learning retrieval knowledge from data.
    Vitenskapelig kapittel

1998

  • Langseth, Helge; Lindqvist, Bo Henry. (1998) Uncertainty Bounds for a Monotone Multistate System. Probability in the Engineering and Informational Science
    Populærvitenskapelig artikkel
  • Langseth, Helge; Haugen, Knut E.; Sandtorv, Helge A.. (1998) Analysis of OREDA Data for Maintenance Optimisation. Reliability Engineering & System Safety
    Vitenskapelig artikkel
  • Aamodt, Agnar; Langseth, Helge. (1998) Integrating Bayesian networks into knowledge-intensive CBR.
    Vitenskapelig kapittel
  • Langseth, Helge; Lindqvist, Bo Henry. (1998) Uncertainty bounds for a monotone multistate system. Probability in the engineering and informational sciences (Print)
    Vitenskapelig artikkel

Tidsskriftspublikasjoner

  • Bjøru, Anna Rodum; Lysnæs-Larsen, Jacob; Jørgensen, Oskar; Strumke, Inga; Langseth, Helge. (2026) A framework for causal concept-based model explanations. Frontiers in Artificial Intelligence
    Vitenskapelig artikkel
  • Bekkemoen, Yanzhe; Langseth, Helge. (2025) Interpretable Deep Reinforcement Learning Via Concept-Based Policy Distillation. Machine Learning
    Vitenskapelig artikkel
  • Danelakis, Antonios; Langseth, Helge; Nachev, Parashkev; Nelson, Amy; Bjørk, Marte-Helene; Matharu, Manjit Singh; Tronvik, Erling Andreas; May, Arne; Stubberud, Anker. (2024) What predicts citation counts and translational impact in headache research? A machine learning analysis. Cephalalgia
    Vitenskapelig artikkel
  • Masegosa, Andres R.; Nielsen, Thomas D.; Langseth, Helge; Ramos-López, Dario; Salmeron, Antonio; Madsen, Anders L.. (2017) Bayesian Models of Data Streams with Hierarchical Power Priors. JMLR Workshop and Conference Proceedings
    Vitenskapelig artikkel
  • Stubberud, Anker; Langseth, Helge; Nachev, Parashkev; Matharu, Manjit S.; Tronvik, Erling Andreas. (2024) Artificial intelligence and headache. Cephalalgia
    Vitenskapelig oversiktsartikkel
  • Bjøru, Anna Rodum; Cabañas, Rafael; Langseth, Helge; Salmeron, Antonio. (2025) Divide and conquer for causal computation. International Journal of Approximate Reasoning
    Vitenskapelig artikkel
  • Nielsen, Thomas D.; Hovda, Sigve; Fernandez, Antonio; Langseth, Helge; Madsen, Anders L.; Masegosa, Andres; Salmeron, Antonio. (2014) Requirement Engineering for a Small Project with Pre-Specified Scope. NIKT: Norsk IKT-konferanse for forskning og utdanning
    Vitenskapelig artikkel
  • Cabañas, Rafael; Martínez, Ana M.; Masegosa, Andres R.; Ramos-López, Darío; Salmerón, Antonio; Nielsen, Thomas D.; Langseth, Helge; Madsen, Anders L.. (2017) Financial data analysis with PGMs using AMIDST. IEEE International Conference on Data Mining Workshops, ICDMW
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2009) Maximum Likelihood Learning of Conditional MTE Distributions. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.. (2003) Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains. Journal of machine learning research
    Vitenskapelig artikkel
  • Masegosa, Andres; Martinez, Ana M.; Ramos-López, Dario; Cabañas, Rafael; Salmerón, Antonio; Langseth, Helge; Nielsen, Thomas D.; Madsen, Anders L.. (2018) AMIDST: A Java toolbox for scalable probabilistic machine learning. Knowledge-Based Systems
    Vitenskapelig artikkel
  • Salmeron, Antonio; Ramoz-López, Darío; Borchani, Hanen; Martinez, Ana M.; Masegosa, Andres; Fernandez, Antonio; Langseth, Helge; Madsen, Anders L.; Nielsen, Thomas D.. (2015) Parallel importance sampling in conditional linear gaussian networks. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Masegosa, Andres; Cabañas, Rafael; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio. (2021) Probabilistic Models with Deep Neural Networks. Entropy
    Vitenskapelig artikkel
  • da Silva, Eliezer de Souza; Langseth, Helge; Ramampiaro, Heri. (2017) Content-Based Social Recommendation with Poisson Matrix Factorization. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Langseth, Helge; Lindqvist, Bo Henry. (1998) Uncertainty Bounds for a Monotone Multistate System. Probability in the Engineering and Informational Science
    Populærvitenskapelig artikkel
  • Salmeron, Antonio; Langseth, Helge; Masegosa, Andres; Nielsen, Thomas D.. (2022) A Reparameterization of Mixtures of Truncated Basis Functions and its Applications. Proceedings of Machine Learning Research (PMLR)
    Vitenskapelig artikkel
  • Killingberg, Ludvig; Langseth, Helge. (2023) The Multiquadric Kernel for Moment-Matching Distributional Reinforcement Learning. Transactions on Machine Learning Research (TMLR)
    Vitenskapelig artikkel
  • Saleh Salem, Tárik; Kathuria, Karan; Ramampiaro, Heri; Langseth, Helge. (2019) Forecasting Intra-Hour Imbalances in Electric Power Systems. Proceedings of the AAAI Conference on Artificial Intelligence
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2009) Inference in Hybrid Bayesian Networks. Reliability Engineering & System Safety
    Vitenskapelig artikkel
  • Jensen, Finn V.; Kjærulff, Uffe; Langseth, Helge; Scaanning, Claus; Vomlelova, Marta; Vomlel, Jiri. (2001) The SACSO methodology for troubleshooting complex systems. Artificial intelligence for engineering design, analysis and manufacturing
    Vitenskapelig artikkel
  • Mathisen, Bjørn Magnus; Aamodt, Agnar; Langseth, Helge; Bach, Kerstin. (2019) Learning similarity measures from data. Progress in Artificial Intelligence
    Vitenskapelig artikkel
  • Tiwari, Shweta; Bell, Gavin; Langseth, Helge; Ramampiaro, Heri. (2022) Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches. Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART)
    Vitenskapelig artikkel
  • Langseth, Helge; Bangsø, Olav. (2001) Parameter Learning in Object Oriented Bayesian Networks. Annals of Mathematics and Artificial Intelligence
    Vitenskapelig artikkel
  • Bjøru, Anna Rodum; Cabañas, Rafael; Langseth, Helge; Salmerón, Antonio. (2024) A Divide and Conquer Approach for Solving Structural Causal Models. Proceedings of Machine Learning Research (PMLR)
    Vitenskapelig artikkel
  • Ramos-López, Dario; Masegosa, Andres R.; Martinez, Ana M.; Salmeron, Antonio; Nielsen, Thomas D.; Langseth, Helge; Madsen, Anders L.. (2017) MAP inference in dynamic hybrid Bayesian networks. Progress in Artificial Intelligence
    Vitenskapelig artikkel
  • Hokstad, Per; Langseth, Helge; Lindqvist, Bo Henry; Vatn, Jørn. (2005) Failure modeling and maintenance optimization for a railway line. International Journal of Performability Engineering
    Vitenskapelig artikkel
  • Salmeron, Antonio; Rumi, Rafael; Langseth, Helge; Nielsen, Thomas D.; Madsen, Anders L.. (2018) A Review of Inference Algorithms for Hybrid Bayesian Networks. The journal of artificial intelligence research
    Vitenskapelig oversiktsartikkel
  • Madsen, Anders L.; Jensen, Frank; Salmeron, Antonio; Langseth, Helge; Nielsen, Thomas D.. (2017) A parallel algorithm for Bayesian network structure learning from large data sets. Knowledge-Based Systems
    Vitenskapelig artikkel
  • Ramos-Lopez, Dario; Salmeron, Antonio; Rumi, Rafel; Martinez, Ana M.; Nielsen, Thomas D.; Masegosa Arredondo, Andres Ramon; Langseth, Helge; Madsen, Anders L.. (2016) Scalable MAP inference in Bayesian networks based on a Map-Reduce approach. Journal of machine learning research
    Vitenskapelig artikkel
  • Mathisen, Bjørn Magnus; Aamodt, Agnar; Langseth, Helge. (2017) Data driven case base construction for prediction of success of marine operations. CEUR Workshop Proceedings
    Vitenskapelig artikkel
  • Lindqvist, Bo Henry; Støve, Bård; Langseth, Helge. (2006) Modelling of dependence between critical failure and preventive maintenance: The repair alert model. Journal of Statistical Planning and Inference
    Vitenskapelig artikkel
  • Langseth, Helge; Portinale, Luigi. (2007) Bayesian Networks in Reliability. Reliability Engineering & System Safety
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.. (2006) Classification using Hierarchical Naïve Bayes models. Machine Learning
    Vitenskapelig artikkel
  • Langseth, Helge; Haugen, Knut E.; Sandtorv, Helge A.. (1998) Analysis of OREDA Data for Maintenance Optimisation. Reliability Engineering & System Safety
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.. (2012) A latent model for collaborative filtering. International Journal of Approximate Reasoning
    Vitenskapelig artikkel
  • Langseth, Helge; Lindqvist, Bo Henry. (2006) Competing risks for repairable systems: A data study. Journal of Statistical Planning and Inference
    Vitenskapelig artikkel
  • Ramos-López, Dario; Masegosa, Andres R.; Salmerón, Antonio; Rumi, Rafael; Langseth, Helge; Nielsen, Thomas D.; Madsen, Anders L.. (2018) Scalable importance sampling estimation of Gaussian mixture posteriors in Bayesian networks. International Journal of Approximate Reasoning
    Vitenskapelig artikkel
  • Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2010) Architectures Integrating Case-Based Reasoning and Bayesian Networks for Clinical Decision Support. IFIP Advances in Information and Communication Technology
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.. (2009) Latent Classification Models for Binary Data. Pattern Recognition
    Vitenskapelig artikkel
  • Swider, Anna; Langseth, Helge; Pedersen, Eilif. (2019) Application of data-driven models in the analysis of marine power systems. Applied Ocean Research
    Vitenskapelig artikkel
  • Lillegraven, Terje N.; Wolden, Arnt C.; Kofod-Petersen, Anders; Langseth, Helge. (2011) A design for a tourist CF system. Frontiers in Artificial Intelligence and Applications
    Konferanseabstract
  • Masegosa, Andres; Ramos-López, Dario; Salmeron, Antonio; Langseth, Helge; Nielsen, Thomas D.. (2020) Variational Inference over Nonstationary Data Streams for Exponential Family Models. Mathematics
    Vitenskapelig artikkel
  • Masegosa, Andres; Martinez, Ana M.; Ramos-López, Dario; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio. (2020) Analyzing concept drift: A case study in the financial sector. Intelligent Data Analysis
    Vitenskapelig artikkel
  • Borchani, Hanen; Martinez, Ana M.; Masegosa, Andres; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio; Fernandez, Antonio; Madsen, Anders L.; Sáez, Ramón. (2015) Modeling concept drift: A probabilistic graphical model based approach. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Masegosa, Andres; Martinez, Ana M.; Ramos-López, Dario; Cabañas, Rafael; Salmeron, Antonio; Langseth, Helge; Nielsen, Thomas D.. (2019) AMIDST: A Java toolbox for scalable probabilistic machine learning. Knowledge-Based Systems
    Vitenskapelig artikkel
  • Ramos-López, Dario; Salmeron, Antonio; Rumi, Rafael; Martinez, Ana M.; Nielsen, Thomas D.; Masegosa, Andres R.; Langseth, Helge; Madsen, Anders L.. (2016) Scalable MAP inference in Bayesian networks based on a Map-Reduce approach. Journal of machine learning research
    Vitenskapelig artikkel
  • Masegosa, Andres R.; Martinez, Ana M.; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio; Ramos-López, Dario; Madsen, Anders L.. (2016) d-VMP: Distributed Variational Message Passing. Journal of machine learning research
    Vitenskapelig artikkel
  • Madsen, Anders L.; Jensen, Frank; Salmeron, Antonio; Langseth, Helge; Nielsen, Thomas D.. (2015) Parallelization of the PC Algorithm. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Danelakis, Antonios; Kumelj, Tjasa; Winsvold, Bendik S.; Bjørk, Marte Helene; Nachev, Parashkev; Matharu, Manjit; Giles, Dominic; IHGC, Int. Headache Genetic Cons.; Tronvik, Erling Andreas; Langseth, Helge. (2025) Diagnosing migraine from genome-wide genotype data: a machine learning analysis. Brain
    Vitenskapelig artikkel
  • Agarwal, Basant; Ramampiaro, Heri; Langseth, Helge; Ruocco, Massimiliano. (2018) A deep network model for paraphrase detection in short text messages. Information Processing & Management
    Vitenskapelig artikkel
  • Borchani, Hanen; Martinez, Ana M.; Masegosa, Andres; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio; Fernández, Antonio; Madsen, Anders L.; Sáez, Ramón. (2015) Dynamic Bayesian modeling for risk prediction in credit operations. Frontiers in Artificial Intelligence and Applications
    Vitenskapelig artikkel
  • Vassøy, Bjørnar; Kille, Benjamin Uwe; Langseth, Helge. (2025) Opt-in Transparent Fairness for Recommender Systems. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Andersen, Martin Lieberkind; Sævik, Svein; Wu, Jie; Leira, Bernt Johan; Langseth, Helge. (2024) Simulating Vortex-Induced Vibrations in Sheared Current by Using an Empirical Time-Domain Model with Adaptive Parameters. Applied Ocean Research
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.. (2005) Latent classification models. Machine Learning
    Vitenskapelig artikkel
  • Andersen, Martin Lieberkind; Sævik, Svein; Wu, Jie; Leira, Bernt Johan; Langseth, Helge. (2024) Applying Bayesian optimization to predict parameters in a time-domain model for cross-flow vortex-induced vibrations. Marine Structures
    Vitenskapelig artikkel
  • Langseth, Helge; Marquez, David; Neil, Martin. (2013) Fast approximate inference in hybrid Bayesian networks using dynamic discretisation. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2012) Mixtures of truncated basis functions. International Journal of Approximate Reasoning
    Vitenskapelig artikkel
  • Vassøy, Bjørnar; Langseth, Helge. (2024) Consumer-side fairness in recommender systems: a systematic survey of methods and evaluation. Artificial Intelligence Review
    Vitenskapelig oversiktsartikkel
  • Salmerón, Antonio; Madsen, Anders L.; Jensen, Frank; Langseth, Helge; Nielsen, Thomas D.; Ramos-López, Dario; Martínez, Ana M.; Masegosa, Andres R.. (2016) Parallel filter-based feature selection based on balanced incomplete block designs. Frontiers in Artificial Intelligence and Applications
    Vitenskapelig artikkel
  • Bekkemoen, Yanzhe; Langseth, Helge. (2024) ASAP: Attention-Based State Space Abstraction for Policy Summarization. Proceedings of Machine Learning Research (PMLR)
    Vitenskapelig artikkel
  • Zhong, Shengtong; Langseth, Helge; Nielsen, Thomas D.. (2014) A classification-based approach to monitoring the safety of dynamic systems. Reliability Engineering & System Safety
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.; Pérez-Bernabé, Inmaculada; Salmeron, Antonio. (2014) Learning mixtures of truncated basis functions from data. International Journal of Approximate Reasoning
    Vitenskapelig artikkel
  • Masegosa, Andres R.; Martinez, Ana M.; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio; Ramos-López, Dario; Madsen, Anders L.. (2017) Scaling up Bayesian variational inference using distributed computing clusters. International Journal of Approximate Reasoning
    Vitenskapelig artikkel
  • Nguyen, Hai Thanh; Almenningen, Thomas; Havig, Martin; Schistad, Herman; Kofod-Petersen, Anders; Langseth, Helge; Ramampiaro, Heri. (2014) Learning to Rank for Personalized Fashion Recommender Systems via Implicit Feedback. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.. (2015) Scalable learning of probabilistic latent models for collaborative filtering. Decision Support Systems
    Vitenskapelig artikkel
  • Houeland, Tor Gunnar Høst; Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2011) Combining CBR and BN using metareasoning. Frontiers in Artificial Intelligence and Applications
    Vitenskapelig artikkel
  • Aftab, Sofia; Ramampiaro, Heri; Langseth, Helge; Ruocco, Massimiliano. (2023) Deep Contextual Grid Triplet Network for Context-Aware Recommendation. IEEE Access
    Vitenskapelig artikkel
  • Killingberg, Ludvig; Langseth, Helge. (2023) Bayesian Exploration in Deep Reinforcement Learning. CEUR Workshop Proceedings
    Vitenskapelig artikkel
  • Saleh Salem, Tárik; Langseth, Helge; Ramampiaro, Heri. (2020) Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles. Proceedings of Machine Learning Research (PMLR)
    Vitenskapelig artikkel
  • Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2010) Parameter Estimation and Model Selection for Mixtures of Truncated Exponentials. International Journal of Approximate Reasoning
    Vitenskapelig artikkel
  • Langseth, Helge; Jensen, Finn V.. (2003) Decision Theoretic Troubleshooting of Coherent Systems. Reliability Engineering & System Safety
    Vitenskapelig artikkel
  • Pitsilis, Georgios; Ramampiaro, Heri; Langseth, Helge. (2018) Effective hate-speech detection in Twitter data using recurrent neural networks. Applied Intelligence - The International Journal of Research on Intelligent Systems for Real Life Complex Problems
    Vitenskapelig artikkel
  • Langseth, Helge; Lindqvist, Bo Henry. (1998) Uncertainty bounds for a monotone multistate system. Probability in the engineering and informational sciences (Print)
    Vitenskapelig artikkel
  • Lindqvist, Bo; Støve, Bård; Langseth, Helge. (2006) Modelling of dependence between critical failure and preventive maintenance: The repair alert model. Journal of Statistical Planning and Inference
    Vitenskapelig artikkel
  • Salmeron, Antonio; Rumi, Rafael; Langseth, Helge; Madsen, Anders L.; Nielsen, Thomas D.. (2015) MPE inference in Conditional Linear Gaussian Networks. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel
  • Høverstad, Boye Annfelt; Tidemann, Axel; Langseth, Helge; Øzturk, Pinar. (2015) Short-Term Load Forecasting With Seasonal Decomposition Using Evolution for Parameter Tuning. IEEE Transactions on Smart Grid
    Vitenskapelig artikkel
  • Tiwari, Shweta; Ramampiaro, Heri; Langseth, Helge. (2021) Machine Learning in Financial Market Surveillance: A Survey. IEEE Access
    Vitenskapelig oversiktsartikkel
  • Pérez-Bernabé, Inmaculada; Salmeron, Antonio; Langseth, Helge. (2015) Learning conditional distributions using mixtures of truncated basis functions. Lecture Notes in Computer Science (LNCS)
    Vitenskapelig artikkel

Bøker

  • Ruocco, Massimiliano; Skrede, Ole Steinar Lillestøl; Langseth, Helge. (2017) Inter-Session Modeling for Session-Based Recommendation. Association for Computing Machinery (ACM)
    Antologi
  • Kofod-Petersen, Anders; Heintz, Fredrik; Langseth, Helge. (2011) Eleventh Scandinavian Conference on Artificial Intelligence -- SCAI 2011. IOS Press
    Antologi
  • Kofod-Petersen, Anders; Langseth, Helge; Gundersen, Odd Erik. (2009) Proceedings of the First Norwegian Artificial Intelligence Symposium. Tapir Akademisk Forlag
    Antologi
  • Kofod-Pedersen, Anders; Langseth, Helge; Gundersen, Odd Erik. (2009) Proceedings of the First Norwegian Artificial Intelligence Symposium. Tapir Akademisk Forlag
    Antologi
  • Langseth, Helge; Cojazzi, Giacomo G.M.. (2007) Reliability of Safety-Critical Systems: Proceedings of the 30th ESReDA Seminar Hosted by SINTEF, Trondheim, Norway June 7-8, 2006. Office for Official publications of the European communities
    Antologi
  • Kofod-Petersen, Anders; Langseth, Helge; Gundersen, Odd Erik. (2009) Proceedings of the first Norwegian Artificial Intelligence Symposium. Tapir Akademisk Forlag
    Antologi

Del av bok/rapport

  • Zhong, Shengtong; Martinez, Ana M.; Nielsen, Thomas D.; Langseth, Helge. (2010) Towards a More Expressive Model for Dynamic Classification.
    Vitenskapelig kapittel
  • Høiem, Kristian Wang; Santi, Vemund Mehl; Torsæter, Bendik Nybakk; Langseth, Helge; Andresen, Christian Andre; Rosenlund, Gjert Hovland. (2020) Comparative Study of Event Prediction in Power Grids using Supervised Machine Learning Methods.
    Vitenskapelig kapittel
  • Myklatun, Øyvind Herstad; Thorrud, Thorstein Kaldahl; Nguyen, Hai Thanh; Langseth, Helge; Kofod-Petersen, Anders. (2015) Probability-based Approach for Predicting E-commerce Consumer Behaviour Using Sparse Session Data.
    Vitenskapelig kapittel
  • Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio. (2012) Learning Mixtures of Truncated Basis Functions from Data.
    Vitenskapelig kapittel
  • Kofod-Petersen, Anders; Langseth, Helge; Gundersen, Odd Erik. (2009) Preface.
    Innledning i antologi
  • Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2012) Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions.
    Vitenskapelig kapittel
  • Bjørkvoll, Thor; Langseth, Helge. (2004) The Prioritization of Risk Reducing Measures in View of Uncertain Cost/Benefits.
    Vitenskapelig kapittel
  • Høverstad, Boye Annfelt; Tidemann, Axel; Langseth, Helge. (2013) Effects of data cleansing on load prediction algorithms.
    Vitenskapelig kapittel
  • Tidemann, Axel; Høverstad, Boye Annfelt; Langseth, Helge; Øzturk, Pinar. (2013) Effects of scale on load prediction algorithms.
    Vitenskapelig kapittel
  • Langseth, Helge; Jensen, Finn V.. (2008) Bayesian Networks and Decision Graphs in Reliability.
    Vitenskapelig kapittel
  • Langseth, Helge; Lindqvist, Bo Henry. (2003) A maintenance model for components exposed to several failure mechanisms and imperfect repair.
    Vitenskapelig kapittel
  • Lindqvist, Bo Henry; Langseth, Helge. (2005) Statistical modelling and inference for component failure times under preventive maintenance and independent censoring.
    Vitenskapelig kapittel
  • Langseth, Helge. (2008) Bayesian networks in Reliability: The Good, The Bad, and The Ugly.
    Vitenskapelig kapittel
  • Ramampiaro, Heri; Langseth, Helge; Almenningen, Thomas; Schistad, Herman; Havig, Martin Christian; Nguyen, Hai Thanh. (2019) New Ideas in Ranking for Personalized Fashion Recommender Systems.
    Vitenskapelig kapittel
  • Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2010) Architectures integrating case-based reasoning and Bayesian networks for clinical decision support.
    Vitenskapelig kapittel
  • Vassøy, Bjørnar; Langseth, Helge; Kille, Benjamin Uwe. (2023) Providing Previously Unseen Users Fair Recommendations Using Variational Autoencoders.
    Vitenskapelig kapittel
  • Langseth, Helge; Aamodt, Agnar; Winnem, Ole Martin. (1999) Learning retrieval knowledge from data.
    Vitenskapelig kapittel
  • Langseth, Helge; Portinale, Luigi. (2007) Applications of Bayesian Networks in Reliability Analysis.
    Vitenskapelig kapittel
  • Kofod-Petersen, Anders; Langseth, Helge; Aamodt, Agnar. (2010) Explanations in Bayesian networks using provenance through case-based reasoning.
    Vitenskapelig kapittel
  • Andersen, Martin Lieberkind; Sævik, Svein; Leira, Bernt Johan; Wu, Jie; Langseth, Helge; Passano, Elizabeth Anne; Lie, Halvor; Yin, Decao. (2022) Estimation of VIV-parameters based on Response Measurements and Bayesian Machine Learning Algorithms.
    Vitenskapelig kapittel
  • Gundersen, Odd Erik; Shamsaliei, Saeid; Kjærnli, Håkon Slåtten; Langseth, Helge. (2023) On Reporting Robust and Trustworthy Conclusions from Model Comparison Studies Involving Neural Networks and Randomness.
    Vitenskapelig kapittel
  • Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2009) Maximum Likelihood Learning of Conditional MTE Distributions.
    Vitenskapelig kapittel
  • Madsen, Anders L.; Jensen, Frank; Salmeron, Antonio; Karlsen, Martin; Langseth, Helge; Nielsen, Thomas D.. (2014) A New Method for Vertical Parallelisation of TAN Learning Based on Balanced Incomplete Block Designs.
    Vitenskapelig kapittel
  • Vatn, Jørn; Langseth, Helge. (2006) Estimation of Weibull parameters when the i.i.d. assumption does not hold.
    Vitenskapelig kapittel
  • Fernandez, Antonio; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio. (2010) Parameter learning in MTE networks using incomplete data.
    Vitenskapelig kapittel
  • Kofod-Petersen, Anders; Langseth, Helge. (2010) Tourist Without a Cause.
    Vitenskapelig kapittel
  • Aamodt, Agnar; Langseth, Helge. (1998) Integrating Bayesian networks into knowledge-intensive CBR.
    Vitenskapelig kapittel
  • Langseth, Helge. (2013) Beating the bookie: A look at statistical models for prediction of football matches.
    Vitenskapelig kapittel
  • Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2011) A hybrid CBR and BN architecture refined through data analysis.
    Vitenskapelig kapittel
  • Kofod-Petersen, Anders; Heintz, Fredrik; Langseth, Helge. (2011) Foreword.
    Innledning i antologi
  • Zhong, Shengtong; Langseth, Helge. (2009) Local-Global-Learning of Naive Bayesian Classifier.
    Vitenskapelig kapittel
  • Baumgartner, David; Langseth, Helge; Ramampiaro, Heri; Engø-Monsen, Kenth. (2023) mTADS: Multivariate Time Series Anomaly Detection Benchmark Suites.
    Vitenskapelig kapittel
  • Langseth, Helge. (2009) Bayesian Networks for Collaborative Filtering.
    Vitenskapelig kapittel
  • Zeng, Ming; Gao, Haoxiang; Yu, Tong; Mengshoel, Ole Jakob; Langseth, Helge; Lane, Ian; Liu, Xiaobing. (2018) Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention.
    Vitenskapelig kapittel

Rapport

  • Langseth, Helge; Nielsen, Thomas D.. (2009) A latent model for collaborative filtering. Aalborg Universitetsforlag
    Forskningsrapport

Studentoppgave eller avhandling

  • Bjøru, Anna Rodum; Langseth, Helge; Strumke, Inga; Bach, Kerstin. (2026) Causal Post-hoc Explainable AI. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling
  • Vassøy, Bjørnar; Langseth, Helge; Kille, Benjamin Uwe; Vinterbo, Staal Amund. (2026) Consumer-side Fairness in Recommender Systems. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling
  • Aftab, Sofia; Ramampiaro, Heri; Langseth, Helge; Ruocco, Massimiliano. (2025) Improving Top-N Recommendations: Leveraging Pair-Wise Deep Learning Methods and Evaluation Metrics Contextual modeling, Pair-wise loss functions and Metric enhancement. NTNU Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling
  • Bekkemoen, Yanzhe; Langseth, Helge. (2021) Correcting Classification: A Bayesian Framework Using Explanation Feedback to Improve Classification Abilities. Norges teknisk-naturvitenskapelige universitet
    Masteroppgave
  • Mathisen, Bjørn Magnus; Aamodt, Agnar; Bach, Kerstin; Langseth, Helge. (2021) Using similarity learning to enable decision support in aquaculture. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling
  • Kvamme, Johannes; Larsen, Pål-Edward; Langseth, Helge. (2021) Achieving Trustable Explanations Through Multi-Task Learning Neural Networks. Norges teknisk-naturvitenskapelige universitet
    Masteroppgave
  • Langseth, Helge. (2002) Bayesian networks with applications in reliability analysis. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling
  • da Silva, Eliezer de Souza; Langseth, Helge; Ramampiaro, Heri. (2021) Factorization models with relational and contextual information: Probabilistic factorization, Point processes and neural sequential models. Norwegian University of Science and Technology
    Doktoravhandling
  • Langseth, Helge; Høijord, Espen Hansen. (2022) Explainable AI (XAI) for grid loss forecasting. Norges teknisk-naturvitenskapelige universitet
    Masteroppgave
  • Langseth, Helge; Bekkemoen, Yanzhe. (2025) Explainable Reinforcement Learning (XRL): Simplifying Agent Behavior. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling
  • Myhre, Henrik; Matsen, Erik; Langseth, Helge. (2023) Making Sense of Tabular Neural Networks: Interpretability using Concept Detection. NTNU
    Masteroppgave
  • Hanssen, Jørgen; Langseth, Helge. (2023) Expanding Our Knowledge of Maritime Trade with AIS and Explainable AI Systems. Norges teknisk-naturvitenskapelige universitet
    Masteroppgave
  • Flogard, Eirik Lund; Mengshoel, Ole Jakob; Langseth, Helge; Ramampiaro, Heri; Bach, Kerstin. (2024) Improving Labour Inspection Efficiency via Machine Learning. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling
  • Herland, Sverre; Bach, Kerstin; Misimi, Ekrem; Langseth, Helge. (2025) Reinforcement Learning for Robotic Control and Manipulation in Ocean Space Applications. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling

Undervisning

Emner

  • TDT4171 - Metoder i kunstig intelligens
  • DT8122 - Probabilistisk kunstig intelligens

Formidling

2024

  • Konferanseforedrag
    Danelakis, Antonios; Stubberud, Anker; Winsvold, Bendik Kristoffer Slagsvold; bjørk, marte helene; Giles, Dominic; Nachev, Parashkev; Kumelj, Tjasa; Hagen, Knut; Matharu, Manjit; Nyholt, Dale R.. (2024) Machine learning versus polygenic risk scoring as migraine predictors based on genome-wide genotype data. Migraine Trust International Symposium (MTIS) 2024
  • Konferanseforedrag
    Danelakis, Antonios; Abildsnes, Håkon Kvisle; Faisal, Fahim; Winsvold, Bendik Kristoffer Slagsvold; bjørk, marte helene; Giles, Dominic; Nachev, Parashkev; Kumelj, Tjasa; Hagen, Knut; Matharu, Manjit. (2024) Machine learning can predict migraine from genotype and non-headache clinical data with high accuracy. European Headache Congress (EHC) 2024

2023

  • Konferanseforedrag
    Bekkemoen, Yanzhe; Langseth, Helge. (2023) ASAP: Attention-Based State Space Abstraction for Policy Summarization. The 15th Asian Conference on Machine Learning
  • Konferanseposter
    Vassøy, Bjørnar; Langseth, Helge; Kille, Benjamin Uwe. (2023) Providing Previously Unseen Users Fair Recommendations Using Variational Autoencoders. ACM RecSys 2023

2022

  • Konferanseforedrag
    Salmeron, Antonio; Langseth, Helge; Masegosa, Andres; Nielsen, Thomas D.. (2022) A Reparameterization of Mixtures of Truncated Basis Functions and its Applications. International Conference on Probabilistic Graphical Models
  • Intervju
    Langseth, Helge. (2022) Skal vi godta at våpen sjølv bestemmer når dei skal drepe?.

2021

  • Intervju
    Langseth, Helge. (2021) Spotifys makt over dine lyttervaner.

2020

  • Intervju
    Holter, Trym; Langseth, Helge. (2020) Ønsker å gjøre kunstig intelligens mer forståelig.
  • Intervju
    Langseth, Helge. (2020) Nå blir terskelen enda lavere for nordmenn som vil lære om kunstig intelligens.

2019

  • Intervju
    Langseth, Helge. (2019) Opprop mot dødelige autonome våpen.

2018

  • Konferanseforedrag
    Zeng, Ming; Gao, Haoxiang; Yu, Tong; Mengshoel, Ole Jakob; Langseth, Helge; Lane, Ian; Liu, Xiaobing. (2018) Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention. 2018 ACM International Symposium on Wearable Computers

2017

  • Konferanseforedrag
    Mathisen, Bjørn Magnus; Aamodt, Agnar; Langseth, Helge. (2017) Data driven case base construction for prediction of success of marine operations. ICCBR-17 Workshop on Workshop on Case-based Reasoning and Deep Learning - CBRDL 2017

2015

  • Foredrag
    Langseth, Helge. (2015) Research Frontiers in Recommender Systems. AI and BigData in a Digital World
  • Foredrag
    Langseth, Helge. (2015) Big Data: En kunst å hente kunnskap ut av store tall?. TEKMAR
  • Intervju
    Langseth, Helge; Bjørkeng, Per Kristian. (2015) Dyp læring: Slik har maskinene begynt å lære som oss.
  • Konferanseforedrag
    Masegosa, Andres; Martinez, Ana M.; Borchani, Hanen; Ramos-Lopez, Dario; Nielsen, Thomas D.; Langseth, Helge; Salmeron, Antonio; Madsen, Anders L.. (2015) AMIDST: Analysis of MassIve Data STreams. 27th Benelux Conference on Artificial Intelligence

2013

  • Konferanseforedrag
    Langseth, Helge; Marquez, David; Neil, Martin. (2013) Fast approximate inference in hybrid Bayesian networks using dynamic discretisation. 5th. INTERNATIONAL WORK-CONFERENCE on the INTERPLAY between NATURAL and ARTIFICIAL COMPUTATION
  • Konferanseforedrag
    Langseth, Helge. (2013) Beating the bookie: A look at statistical models for prediction of football matches. The 12th Scandinavian AI conference

2012

  • Konferanseforedrag
    Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio. (2012) Learning Mixtures of Truncated Basis Functions from Data. The Sixth European Workshop on Probabilistic Graphical Models
  • Konferanseforedrag
    Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2012) Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions. The Sixth European Workshop on Probabilistic Graphical Models

2011

  • Konferanseforedrag
    Lillegraven, Terje N.; Wolden, Arnt C.; Kofod-Petersen, Anders; Langseth, Helge. (2011) A design for a tourist CF system. Eleventh Scandinavian Conference on Artificial Intelligence
  • Konferanseforedrag
    Houeland, Tor Gunnar Høst; Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2011) Combining CBR and BN using metareasoning. Eleventh Scandinavian Conference on Artificial Intelligence

2010

  • Konferanseforedrag
    Kofod-Petersen, Anders; Langseth, Helge; Aamodt, Agnar. (2010) Explanations in Bayesian Networks using Provenance through Case-based Reasoning. ICCBR 2010 workshop on provenance-aware case-based reasoning (PA-CBR 2010)
  • Konferanseforedrag
    Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2010) Architectures Integrating Case-Based Reasoning and Bayesian Networks for Clinical Decision Support. Intelligent Information Processing (IIP) 2010
  • Konferanseforedrag
    Kofod-Petersen, Anders; Langseth, Helge. (2010) Tourist without a cause. Second Norwegian Artificial Intelligence Symposium
  • Konferanseforedrag
    Fernandez, Antonio; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio. (2010) Parameter learning in MTE networks using incomplete data. The Fifth European Workshop on Probabilistic Graphical Models

2009

  • Konferanseforedrag
    Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2009) Maximum Likelihood Learning of Conditional MTE Distributions. ECSQARU 2009
  • Konferanseforedrag
    Langseth, Helge. (2009) Bayesian Networks for Collaborative Filtering. First Norwegian Artificial Intelligence Symposium

2008

  • Konferanseforedrag
    Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2008) Parameter Estimation in Mixtures of Truncated Exponentials. The Fourth European Workshop on Probabilistic Graphical Models

2007

  • Konferanseforedrag
    Langseth, Helge. (2007) Bayesian Networks in Reliability. Mathematical Methods in Reliability: Methodology and Practice
  • Konferanseforedrag
    Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio; Rumi, Rafael. (2007) Maximum Likelihood vs. Least Squares for Estimating Mixtures of Truncated Exponentials. INFORMS '07

2004

  • Konferanseforedrag
    Langseth, Helge. (2004) Bayesian Networks in Reliability: Some recent developments. The fourth International Conference on Mathematical Models in Reliability, MMR'04

2003

  • Konferanseforedrag
    Langseth, Helge; Lindqvist, Bo Henry. (2003) Competing risk combined with imperfect repair: Some of the dirty details. Workshop on Analysis of Competing Risks - Statistical and Probabilistic Approach.

2002

  • Konferanseforedrag
    Langseth, Helge; Lindqvist, Bo Henry. (2002) Modelling imperfect maintenance and repair of components under competing risk. Third International Conference on Mathematical Methods in Reliability

2001

  • Konferanseforedrag
    Langseth, Helge; Jensen, Finn V.. (2001) Heuristics for two extensions of basic troubleshooting. Seventh scandinavian conference on Artificial Intelligence, SCAI'01
  • Konferanseforedrag
    Bangsø, Olav; Langseth, Helge; Nielsen, Thomas D.. (2001) Structural Learning in Object Oriented Domains. Fourteenth International Florida Artificial Intelligence Research Society Conference

1999

  • Konferanseforedrag
    Langseth, Helge. (1999) Modelling Maintenance for Components under Competing Risk. Tenth European Conference on Safety and Reliability -- ESREL'99
  • Konferanseforedrag
    Langseth, Helge; Aamodt, Agnar; Winnem, Ole Martin. (1999) Learning retrieval knowledge form data. Sixteenth International Joint Conference on Artificial Intelligence

1998

  • Konferanseforedrag
    Langseth, Helge; Aamodt, Agnar. (1998) Integrating Bayesian networks into knowledge intensive CBR. Amerikanske AI-konferansen, AAAI-98
  • Konferanseforedrag
    Langseth, Helge. (1998) Analysis of survival times using Bayesian networks. ESREL'98
  • Konferanseforedrag
    Langseth, Helge. (1998) Analysis of survival times using Bayesian Networks. The ninth European Conference on Safety and Reliability - ESREL'98

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