2022

• Langseth, Helge; Ramampiaro, Herindrasana. (2022) Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches. SciTePress. 2022. ISBN 9789897585470.
• Langseth, Helge; Ramampiaro, Herindrasana. (2022) Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches. SciTePress. 2022. ISBN 9789897585470.
• Tiwari, Shweta; Langseth, Helge; Ramampiaro, Heri; Bell, Gavin. (2022) Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches. Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART). volum 3.

2021

• Masegosa, Andres; Cabañas, Rafael; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio. (2021) Probabilistic Models with Deep Neural Networks. Entropy. volum 23 (1).
• Tiwari, Shweta; Ramampiaro, Heri; Langseth, Helge. (2021) Machine Learning in Financial Market Surveillance: A Survey. IEEE Access. volum 9.

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. 2020 International Conference on Smart Energy Systems and Technologies - SEST.
• 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. volum 24 (3).
• Masegosa, Andres; Ramos-López, Dario; Salmeron, Antonio; Langseth, Helge; Nielsen, Thomas D.. (2020) Variational Inference over Nonstationary Data Streams for Exponential Family Models. Mathematics. volum 8 (11).
• Saleh Salem, Tárik; Langseth, Helge; Ramampiaro, Heri. (2020) Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles. Proceedings of Machine Learning Research (PMLR). volum 124.

2019

• 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. volum 163.
• Mathisen, Bjørn Magnus; Aamodt, Agnar; Langseth, Helge; Bach, Kerstin. (2019) Learning similarity measures from data. Progress in Artificial Intelligence.
• Ramampiaro, Heri; Langseth, Helge; Almenningen, Thomas; Schistad, Herman; Havig, Martin Christian; Nguyen, Hai Thanh. (2019) New Ideas in Ranking for Personalized Fashion Recommender Systems. Business and Consumer Analytics: New Ideas.
• 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. volum 33 (1).
• Swider, Anna; Langseth, Helge; Pedersen, Eilif. (2019) Application of data-driven models in the analysis of marine power systems. Applied Ocean Research. volum 92.

2018

• Agarwal, Basant; Ramampiaro, Heri; Langseth, Helge; Ruocco, Massimiliano. (2018) A deep network model for paraphrase detection in short text messages. Information Processing & Management. volum 54.
• 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. volum 163.
• Pitsilis, Georgios; Ramampiaro, Heri; Langseth, Helge. (2018) Effective hate-speech detection in Twitter data using recurrent neural networks. Applied intelligence (Boston). volum 48 (12).
• 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. volum 100.
• 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. volum 62.
• 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. Proceedings of the 2018 ACM International Symposium on Wearable Computers.

2017

• 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.
• de Souza da Silva, Eliezer; Langseth, Helge; Ramampiaro, Heri. (2017) Content-Based Social Recommendation with Poisson Matrix Factorization. Lecture Notes in Computer Science (LNCS). volum 10534 LNAI.
• 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. volum 117.
• 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. volum 88.
• 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. volum 70.
• Mathisen, Bjørn Magnus; Aamodt, Agnar; Langseth, Helge. (2017) Data driven case base construction for prediction of success of marine operations. CEUR Workshop Proceedings. volum 2028.
• 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. volum 6 (2).
• Ruocco, Massimiliano; Skrede, Ole Steinar Lillestøl; Langseth, Helge. (2017) Inter-Session Modeling for Session-Based Recommendation. Association for Computing Machinery (ACM). 2017. ISBN 978-1-4503-5353-3.

2016

• 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. volum 55.
• 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. volum 52.
• 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. volum 285.

2015

• 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. volum 278.
• 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). volum 9385.
• 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. volum 6 (4).
• Langseth, Helge; Nielsen, Thomas D.. (2015) Scalable learning of probabilistic latent models for collaborative filtering. Decision Support Systems. volum 74.
• Madsen, Anders L.; Jensen, Frank; Salmeron, Antonio; Langseth, Helge; Nielsen, Thomas D.. (2015) Parallelization of the PC Algorithm. Lecture Notes in Computer Science (LNCS). volum 9422.
• 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. RecSys '15 Challenge: Proceedings of the 2015 International ACM Recommender Systems Challenge.
• Pérez-Bernabé, Inmaculada; Salmeron, Antonio; Langseth, Helge. (2015) Learning conditional distributions using mixtures of truncated basis functions. Lecture Notes in Computer Science (LNCS). volum 9161.
• 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). volum 9422.
• 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). volum 9161.

2014

• Langseth, Helge; Nielsen, Thomas D.; Pérez-Bernabé, Inmaculada; Salmeron, Antonio. (2014) Learning mixtures of truncated basis functions from data. International Journal of Approximate Reasoning. volum 55 (4).
• 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. Probabilistic Graphical Models.
• 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). volum 8891.
• 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.
• Zhong, Shengtong; Langseth, Helge; Nielsen, Thomas D.. (2014) A classification-based approach to monitoring the safety of dynamic systems. Reliability Engineering & System Safety. volum 121.

2013

• Høverstad, Boye Annfelt; Tidemann, Axel; Langseth, Helge. (2013) Effects of data cleansing on load prediction algorithms. 2013 IEEE Computational Intelligence Applications in Smart Grid (CIASG).
• Langseth, Helge. (2013) Beating the bookie: A look at statistical models for prediction of football matches. Twelfth Scandinavian Conference on Artificial Intelligence.
• Langseth, Helge; Marquez, David; Neil, Martin. (2013) Fast approximate inference in hybrid Bayesian networks using dynamic discretisation. Lecture Notes in Computer Science (LNCS). volum 7930.
• Tidemann, Axel; Høverstad, Boye Annfelt; Langseth, Helge; Øzturk, Pinar. (2013) Effects of scale on load prediction algorithms. CIRED 2013 Electricity Distribution Systems for a Sustainable Future.

2012

• Langseth, Helge; Nielsen, Thomas D.. (2012) A latent model for collaborative filtering. International Journal of Approximate Reasoning. volum 53 (4).
• Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2012) Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions. Proceedings of the Sixth European Workshop onProbabilistic Graphical Models.
• Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2012) Mixtures of truncated basis functions. International Journal of Approximate Reasoning. volum 53 (2).
• Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio. (2012) Learning Mixtures of Truncated Basis Functions from Data. Proceedings of the Sixth European Workshop onProbabilistic Graphical Models.

2011

• Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2011) A hybrid CBR and BN architecture refined through data analysis. ISDA 2011, Proceedings of the 11th International Conference on Intelligent Systems Design and Applications; 22 – 24 November 2011, Córdoba, Spain.
• Houeland, Tor Gunnar Høst; Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2011) Combining CBR and BN using metareasoning. Frontiers in Artificial Intelligence and Applications. volum 227.
• Kofod-Petersen, Anders; Heintz, Fredrik; Langseth, Helge. (2011) Eleventh Scandinavian Conference on Artificial Intelligence -- SCAI 2011. IOS Press. 2011. ISBN 978-1-60750-753-6. Frontiers in Artificial Intelligence and Applications (227).
• Kofod-Petersen, Anders; Heintz, Fredrik; Langseth, Helge. (2011) Foreword. Eleventh Scandinavian Conference on Artificial Intelligence -- SCAI 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. volum 227.

2010

• 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. volum 340.
• Bruland, Tore; Aamodt, Agnar; Langseth, Helge. (2010) Architectures integrating case-based reasoning and Bayesian networks for clinical decision support. Intelligent Information Processing V.
• Fernandez, Antonio; Langseth, Helge; Nielsen, Thomas D.; Salmeron, Antonio. (2010) Parameter learning in MTE networks using incomplete data. Proceedings of the Fifth European Workshop on Probabilistic Graphical Models (PGM-2010).
• Kofod-Petersen, Anders; Langseth, Helge. (2010) Tourist Without a Cause. Proceedings of the second Norwegian Artificial Intelligence Symposium : November 22, 2010 Høgskolen i Gjøvik.
• Kofod-Petersen, Anders; Langseth, Helge; Aamodt, Agnar. (2010) Explanations in Bayesian networks using provenance through case-based reasoning. ICCBR 2010 Workshop Proceedings.
• 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. volum 51 (5).
• Zhong, Shengtong; Martinez, Ana M.; Nielsen, Thomas D.; Langseth, Helge. (2010) Towards a More Expressive Model for Dynamic Classification. Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference.

2009

• Kofod-Pedersen, Anders; Langseth, Helge; Gundersen, Odd Erik. (2009) Proceedings of the First Norwegian Artificial Intelligence Symposium. Tapir Akademisk Forlag. 2009. ISBN 978-82-519-2519-8.
• Kofod-Petersen, Anders; Langseth, Helge; Gundersen, Odd Erik. (2009) Preface. Proceedings of the First Norwegian Artificial Intelligence Symposium.
• Kofod-Petersen, Anders; Langseth, Helge; Gundersen, Odd Erik. (2009) Proceedings of the First Norwegian Artificial Intelligence Symposium. Tapir Akademisk Forlag. 2009. ISBN 978-82-519-2519-8.
• Kofod-Petersen, Anders; Langseth, Helge; Gundersen, Odd Erik. (2009) Proceedings of the first Norwegian Artificial Intelligence Symposium. Tapir Akademisk Forlag. 2009. ISBN 978-82-519-2519-8.
• Langseth, Helge. (2009) Bayesian Networks for Collaborative Filtering. Proceedings of the First Norwegian Artificial Intelligence Symposium.
• Langseth, Helge; Nielsen, Thomas D.. (2009) A latent model for collaborative filtering. 2009.
• Langseth, Helge; Nielsen, Thomas D.. (2009) Latent Classification Models for Binary Data. Pattern Recognition. volum 42 (11).
• Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2009) Inference in Hybrid Bayesian Networks. Reliability Engineering & System Safety. volum 94 (10).
• Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2009) Maximum Likelihood Learning of Conditional MTE Distributions. Symbolic and Quantitative Approaches to Reasoning with Uncertainty.
• Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio. (2009) Maximum Likelihood Learning of Conditional MTE Distributions. Lecture Notes in Computer Science (LNCS). volum 5590.
• Zhong, Shengtong; Langseth, Helge. (2009) Local-Global-Learning of Naive Bayesian Classifier. Fourth International Conference on Innovative Computing, Information and Control.

2008

• Langseth, Helge. (2008) Bayesian networks in Reliability: The Good, The Bad, and The Ugly. Advances in Mathematical Modeling for Reliability.
• Langseth, Helge; Jensen, Finn V.. (2008) Bayesian Networks and Decision Graphs in Reliability. Encyclopedia of Statistics in Quality and Reliability.

2007

• 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. 2007. ISBN 9789279065743.
• Langseth, Helge; Portinale, Luigi. (2007) Applications of Bayesian Networks in Reliability Analysis. Bayesian Network Technologies: Applications and Graphical Models.
• Langseth, Helge; Portinale, Luigi. (2007) Bayesian Networks in Reliability. Reliability Engineering & System Safety. volum 92 (1).

2006

• Langseth, Helge; Lindqvist, Bo Henry. (2006) Competing risks for repairable systems: A data study. Journal of Statistical Planning and Inference. volum 136 (5).
• Langseth, Helge; Nielsen, Thomas D.. (2006) Classification using Hierarchical Naïve Bayes models. Machine Learning. volum 63 (2).
• 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. volum 136 (5).
• 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. volum 136 (5).
• Vatn, Jørn; Langseth, Helge. (2006) Estimation of Weibull parameters when the i.i.d. assumption does not hold. Ageing of Components and Systems.

2005

• Hokstad, Per; Langseth, Helge; Lindqvist, Bo Henry; Vatn, Jørn. (2005) Failure modeling and maintenance optimization for a railway line. International Journal of Performability Engineering. volum 1 (1).
• Lindqvist, Bo Henry; Langseth, Helge. (2005) Statistical modelling and inference for component failure times under preventive maintenance and independent censoring. Modern Statistical and Mathematical Methods in Reliability.
• Langseth, Helge; Nielsen, Thomas D.. (2005) Latent classification models. Machine Learning. volum 59.

2004

• Bjørkvoll, Thor; Langseth, Helge. (2004) The Prioritization of Risk Reducing Measures in View of Uncertain Cost/Benefits. Probabilistic Safety Assessment and ManagementPSAM 7 - ESREL '04June 14-18, 2004, Berlin, Germany.

2003

• Langseth, Helge; Jensen, Finn V.. (2003) Decision Theoretic Troubleshooting of Coherent Systems. Reliability Engineering & System Safety. volum 80 (1).
• Langseth, Helge; Lindqvist, Bo Henry. (2003) A maintenance model for components exposed to several failure mechanisms and imperfect repair. Mathematical and Statistical Methods in Reliability.
• Langseth, Helge; Nielsen, Thomas D.. (2003) Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains. Journal of machine learning research. volum 4.

2002

• Langseth, Helge. (2002) Bayesian Networks with Applications in Reliability Analysis. Tapir Akademisk Forlag. 2002. ISBN 82-471-5513-3. Doktor ingeniøravhandling : Dr.Ing.avhandling (2002:121).

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. volum 15 (5).
• Langseth, Helge; Bangsø, Olav. (2001) Parameter Learning in Object Oriented Bayesian Networks. Annals of Mathematics and Artificial Intelligence. volum 32 (1/4).

1999

• Langseth, Helge; Aamodt, Agnar; Winnem, Ole Martin. (1999) Learning retrieval knowledge from data. 16th International Conference on Artificial Intelligence (IJCAI 1999), Workshop ML5: Automating the Construction of Case-Based Reasoners, Proceedings.

1998

• Langseth, Helge; Haugen, Knut E.; Sandtorv, Helge A.. (1998) Analysis of OREDA Data for Maintenance Optimisation. Reliability Engineering & System Safety. volum 60 (2).
• Langseth, Helge; Lindqvist, Bo Henry. (1998) Uncertainty Bounds for a Monotone Multistate System. Probability in the Engineering and Informational Science. volum 12.
• Langseth, Helge; Lindqvist, Bo Henry. (1998) Uncertainty bounds for a monotone multistate system. Probability in the engineering and informational sciences (Print). volum 12.
• Aamodt, Agnar; Langseth, Helge. (1998) Integrating Bayesian networks into knowledge-intensive CBR. American Association for Artificial Intelligence (AAAI 1998), Case-Based Reasoning Integrations, Papers from the workshop.