2026

• Bjøru, Anna Rodum; Langseth, Helge; Strumke, Inga; Bach, Kerstin. (2026) Causal Post-hoc Explainable AI. Norges teknisk-naturvitenskapelige universitet
  Doctoral thesis
• 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
  Academic article
• Vassøy, Bjørnar; Langseth, Helge; Kille, Benjamin Uwe; Vinterbo, Staal Amund. (2026) Consumer-side Fairness in Recommender Systems. Norges teknisk-naturvitenskapelige universitet
  Doctoral thesis

2025

• Bekkemoen, Yanzhe; Langseth, Helge. (2025) Interpretable Deep Reinforcement Learning Via Concept-Based Policy Distillation. Machine Learning
  Academic article
• 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
  Doctoral thesis
• Bjøru, Anna Rodum; Cabañas, Rafael; Langseth, Helge; Salmeron, Antonio. (2025) Divide and conquer for causal computation. International Journal of Approximate Reasoning
  Academic article
• 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
  Academic article
• Vassøy, Bjørnar; Kille, Benjamin Uwe; Langseth, Helge. (2025) Opt-in Transparent Fairness for Recommender Systems. Lecture Notes in Computer Science (LNCS)
  Academic article
• Langseth, Helge; Bekkemoen, Yanzhe. (2025) Explainable Reinforcement Learning (XRL): Simplifying Agent Behavior. Norges teknisk-naturvitenskapelige universitet
  Doctoral thesis
• Herland, Sverre; Bach, Kerstin; Misimi, Ekrem; Langseth, Helge. (2025) Reinforcement Learning for Robotic Control and Manipulation in Ocean Space Applications. Norges teknisk-naturvitenskapelige universitet
  Doctoral thesis

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
  Academic article
• Stubberud, Anker; Langseth, Helge; Nachev, Parashkev; Matharu, Manjit S.; Tronvik, Erling Andreas. (2024) Artificial intelligence and headache. Cephalalgia
  Academic literature review
• 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)
  Academic article
• 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
  Academic article
• 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
  Academic article
• Vassøy, Bjørnar; Langseth, Helge. (2024) Consumer-side fairness in recommender systems: a systematic survey of methods and evaluation. Artificial Intelligence Review
  Academic literature review
• Bekkemoen, Yanzhe; Langseth, Helge. (2024) ASAP: Attention-Based State Space Abstraction for Policy Summarization. Proceedings of Machine Learning Research (PMLR)
  Academic article
• Flogard, Eirik Lund; Mengshoel, Ole Jakob; Langseth, Helge; Ramampiaro, Heri; Bach, Kerstin. (2024) Improving Labour Inspection Efficiency via Machine Learning. Norges teknisk-naturvitenskapelige universitet
  Doctoral thesis

2023

• Killingberg, Ludvig; Langseth, Helge. (2023) The Multiquadric Kernel for Moment-Matching Distributional Reinforcement Learning. Transactions on Machine Learning Research (TMLR)
  Academic article
• Vassøy, Bjørnar; Langseth, Helge; Kille, Benjamin Uwe. (2023) Providing Previously Unseen Users Fair Recommendations Using Variational Autoencoders.
  Academic chapter
• 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.
  Academic chapter
• Aftab, Sofia; Ramampiaro, Heri; Langseth, Helge; Ruocco, Massimiliano. (2023) Deep Contextual Grid Triplet Network for Context-Aware Recommendation. IEEE Access
  Academic article
• Killingberg, Ludvig; Langseth, Helge. (2023) Bayesian Exploration in Deep Reinforcement Learning. CEUR Workshop Proceedings
  Academic article
• Myhre, Henrik; Matsen, Erik; Langseth, Helge. (2023) Making Sense of Tabular Neural Networks: Interpretability using Concept Detection. NTNU
  Master thesis
• Hanssen, Jørgen; Langseth, Helge. (2023) Expanding Our Knowledge of Maritime Trade with AIS and Explainable AI Systems. Norges teknisk-naturvitenskapelige universitet
  Master thesis
• Baumgartner, David; Langseth, Helge; Ramampiaro, Heri; Engø-Monsen, Kenth. (2023) mTADS: Multivariate Time Series Anomaly Detection Benchmark Suites.
  Academic chapter

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)
  Academic article
• 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)
  Academic article
• 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.
  Academic chapter
• Langseth, Helge; Høijord, Espen Hansen. (2022) Explainable AI (XAI) for grid loss forecasting. Norges teknisk-naturvitenskapelige universitet
  Master thesis

2021

• Bekkemoen, Yanzhe; Langseth, Helge. (2021) Correcting Classification: A Bayesian Framework Using Explanation Feedback to Improve Classification Abilities. Norges teknisk-naturvitenskapelige universitet
  Master thesis
• Masegosa, Andres; Cabañas, Rafael; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio. (2021) Probabilistic Models with Deep Neural Networks. Entropy
  Academic article
• Mathisen, Bjørn Magnus; Aamodt, Agnar; Bach, Kerstin; Langseth, Helge. (2021) Using similarity learning to enable decision support in aquaculture. Norges teknisk-naturvitenskapelige universitet
  Doctoral thesis
• Kvamme, Johannes; Larsen, Pål-Edward; Langseth, Helge. (2021) Achieving Trustable Explanations Through Multi-Task Learning Neural Networks. Norges teknisk-naturvitenskapelige universitet
  Master thesis
• 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
  Doctoral thesis
• Tiwari, Shweta; Ramampiaro, Heri; Langseth, Helge. (2021) Machine Learning in Financial Market Surveillance: A Survey. IEEE Access
  Academic literature review

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.
  Academic chapter
• Masegosa, Andres; Ramos-López, Dario; Salmeron, Antonio; Langseth, Helge; Nielsen, Thomas D.. (2020) Variational Inference over Nonstationary Data Streams for Exponential Family Models. Mathematics
  Academic article
• 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
  Academic article
• Saleh Salem, Tárik; Langseth, Helge; Ramampiaro, Heri. (2020) Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles. Proceedings of Machine Learning Research (PMLR)
  Academic article

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.
  Academic chapter
• 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
  Academic article
• Mathisen, Bjørn Magnus; Aamodt, Agnar; Langseth, Helge; Bach, Kerstin. (2019) Learning similarity measures from data. Progress in Artificial Intelligence
  Academic article
• Swider, Anna; Langseth, Helge; Pedersen, Eilif. (2019) Application of data-driven models in the analysis of marine power systems. Applied Ocean Research
  Academic article
• 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
  Academic article

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
  Academic article
• 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
  Academic literature review
• 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
  Academic article
• Agarwal, Basant; Ramampiaro, Heri; Langseth, Helge; Ruocco, Massimiliano. (2018) A deep network model for paraphrase detection in short text messages. Information Processing & Management
  Academic article
• 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
  Academic article
• 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.
  Academic chapter

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
  Academic article
• 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
  Academic article
• da Silva, Eliezer de Souza; Langseth, Helge; Ramampiaro, Heri. (2017) Content-Based Social Recommendation with Poisson Matrix Factorization. Lecture Notes in Computer Science (LNCS)
  Academic article
• 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
  Academic article
• 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
  Academic article
• Mathisen, Bjørn Magnus; Aamodt, Agnar; Langseth, Helge. (2017) Data driven case base construction for prediction of success of marine operations. CEUR Workshop Proceedings
  Academic article
• Ruocco, Massimiliano; Skrede, Ole Steinar Lillestøl; Langseth, Helge. (2017) Inter-Session Modeling for Session-Based Recommendation. Association for Computing Machinery (ACM)
  Anthology
• 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
  Academic article

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
  Academic article
• 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
  Academic article
• 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
  Academic article
• 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
  Academic article

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.
  Academic chapter
• 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)
  Academic article
• 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)
  Academic article
• Madsen, Anders L.; Jensen, Frank; Salmeron, Antonio; Langseth, Helge; Nielsen, Thomas D.. (2015) Parallelization of the PC Algorithm. Lecture Notes in Computer Science (LNCS)
  Academic article
• 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
  Academic article
• Langseth, Helge; Nielsen, Thomas D.. (2015) Scalable learning of probabilistic latent models for collaborative filtering. Decision Support Systems
  Academic article
• 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)
  Academic article
• 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
  Academic article
• Pérez-Bernabé, Inmaculada; Salmeron, Antonio; Langseth, Helge. (2015) Learning conditional distributions using mixtures of truncated basis functions. Lecture Notes in Computer Science (LNCS)
  Academic article

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
  Academic article
• 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.
  Academic chapter
• Zhong, Shengtong; Langseth, Helge; Nielsen, Thomas D.. (2014) A classification-based approach to monitoring the safety of dynamic systems. Reliability Engineering & System Safety
  Academic article
• Langseth, Helge; Nielsen, Thomas D.; Pérez-Bernabé, Inmaculada; Salmeron, Antonio. (2014) Learning mixtures of truncated basis functions from data. International Journal of Approximate Reasoning
  Academic article
• 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)
  Academic article

2013

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

2012

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

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
  Conference abstract
• Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2011) A hybrid CBR and BN architecture refined through data analysis.
  Academic chapter
• Kofod-Petersen, Anders; Heintz, Fredrik; Langseth, Helge. (2011) Eleventh Scandinavian Conference on Artificial Intelligence -- SCAI 2011. IOS Press
  Anthology
• Kofod-Petersen, Anders; Heintz, Fredrik; Langseth, Helge. (2011) Foreword.
  Introduction in anthology
• Houeland, Tor Gunnar Høst; Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2011) Combining CBR and BN using metareasoning. Frontiers in Artificial Intelligence and Applications
  Academic article

2010

• Zhong, Shengtong; Martinez, Ana M.; Nielsen, Thomas D.; Langseth, Helge. (2010) Towards a More Expressive Model for Dynamic Classification.
  Academic chapter
• Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2010) Architectures integrating case-based reasoning and Bayesian networks for clinical decision support.
  Academic chapter
• Kofod-Petersen, Anders; Langseth, Helge; Aamodt, Agnar. (2010) Explanations in Bayesian networks using provenance through case-based reasoning.
  Academic chapter
• 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
  Academic article
• Fernandez, Antonio; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio. (2010) Parameter learning in MTE networks using incomplete data.
  Academic chapter
• Kofod-Petersen, Anders; Langseth, Helge. (2010) Tourist Without a Cause.
  Academic chapter
• 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
  Academic article

2009

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

2008

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

2007

• Langseth, Helge; Portinale, Luigi. (2007) Applications of Bayesian Networks in Reliability Analysis.
  Academic chapter
• Langseth, Helge; Portinale, Luigi. (2007) Bayesian Networks in Reliability. Reliability Engineering & System Safety
  Academic article
• 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
  Anthology

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
  Academic article
• Langseth, Helge; Nielsen, Thomas D.. (2006) Classification using Hierarchical Naïve Bayes models. Machine Learning
  Academic article
• Langseth, Helge; Lindqvist, Bo Henry. (2006) Competing risks for repairable systems: A data study. Journal of Statistical Planning and Inference
  Academic article
• Vatn, Jørn; Langseth, Helge. (2006) Estimation of Weibull parameters when the i.i.d. assumption does not hold.
  Academic chapter
• 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
  Academic article

2005

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

2004

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

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
  Academic article
• Langseth, Helge; Lindqvist, Bo Henry. (2003) A maintenance model for components exposed to several failure mechanisms and imperfect repair.
  Academic chapter
• Langseth, Helge; Jensen, Finn V.. (2003) Decision Theoretic Troubleshooting of Coherent Systems. Reliability Engineering & System Safety
  Academic article

2002

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

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
  Academic article
• Langseth, Helge; Bangsø, Olav. (2001) Parameter Learning in Object Oriented Bayesian Networks. Annals of Mathematics and Artificial Intelligence
  Academic article

1999

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

1998

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