Anders L. Madsen

According to our database, Anders L. Madsen authored at least 81 papers between 1998 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Enhancing Control Room Operator Decision Making: An Application of Dynamic Influence Diagrams in Formaldehyde Manufacturing.

Joseph Mietkiewicz, Anders L. Madsen

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2023

A Comparison of Different Marginalization Operations in Simple Propagation.

Anders L. Madsen, Cory J. Butz

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2023

Learning Style Classification by Using Bayesian Networks Based on the Index of Learning Style.

Yeimy Paola Valencia Usme, Marc Normann, Iryna Sapsai, Joerg Abke, Anders L. Madsen, Galia Weidl

Proceedings of the 5th European Conference on Software Engineering Education, 2023

2022

Comparative study of fuzzy-AHP and BBN for spatially-explicit prediction of bark beetle predisposition.

Meryem Tahri, Jan Kaspar, Anders L. Madsen, Roman Modlinger, Khodabakhsh Zabihi, Robert Marusák, Harald Vacik

Environ. Model. Softw., 2022

Stateful to Stateless: Modelling Stateless Ethereum.

Sandra Johnson, David Hyland-Wood, Anders L. Madsen, Kerrie L. Mengersen

Proceedings of the Proceedings Fifth Workshop on Models for Formal Analysis of Real Systems, 2022

Online Updating of Conditional Linear Gaussian Bayesian Networks.

Anders L. Madsen, Kristian G. Olesen, Frank Jensen, Per Henriksen, Thomas Mulvad Larsen, Jørn Munkhof Møller

Proceedings of the International Conference on Probabilistic Graphical Models, 2022

A Decision Support System to Predict Acute Fish Toxicity.

Anders L. Madsen, S. Jannicke Moe, Thomas Braunbeck, Kristin A. Connors, Michelle Embry, Kristin Schirmer, Stefan Scholz, Raoul Wolf, Adam A. Lillicrap

Proceedings of the International Conference on Probabilistic Graphical Models, 2022

2020

Development of a hybrid Bayesian network model for predicting acute fish toxicity using multiple lines of evidence.

S. Jannicke Moe, Anders L. Madsen, Kristin A. Connors, Jane M. Rawlings, Scott E. Belanger, Wayne G. Landis, Raoul Wolf, Adam D. Lillicrap

Environ. Model. Softw., 2020

Multi-criteria decision analysis in Bayesian networks - Diagnosing ecosystem service trade-offs in a hydropower regulated river.

David N. Barton, Håkon Sundt, Ana Adeva-Bustos, Hans-Petter Fjeldstad, Richard D. Hedger, Torbjørn Forseth, Berit Köhler, Øystein Aas, Knut Alfredsen, Anders L. Madsen

Environ. Model. Softw., 2020

A Software System for Predicting Patient Flow at the Emergency Department of Aalborg University Hospital.

Anders L. Madsen, Kristian G. Olesen, Jørn Munkhof Møller, Nicolaj Søndberg-Jeppesen, Frank Jensen, Thomas Mulvad Larsen, Per Henriksen, Morten Lindblad, Trine Søby Christensen

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

Prediction of High Risk of Deviations in Home Care Deliveries.

Anders L. Madsen, Kristian G. Olesen, Heidi Lynge Løvschall, Nicolaj Søndberg-Jeppesen, Frank Jensen, Morten Lindblad, Mads Lause Mogensen, Trine Søby Christensen

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

2019

AMIDST: A Java toolbox for scalable probabilistic machine learning.

Andrés R. Masegosa, Ana M. Martínez, Darío Ramos-López, Rafael Cabañas, Antonio Salmerón, Helge Langseth, Thomas D. Nielsen, Anders L. Madsen

Knowl. Based Syst., 2019

Solving Influence Diagrams with Simple Propagation.

Anders L. Madsen, Cory J. Butz, Jhonatan de S. Oliveira, André E. dos Santos

Proceedings of the Advances in Artificial Intelligence, 2019

Exploiting Symmetry of Independence in d-Separation.

Cory J. Butz, André E. dos Santos, Jhonatan de S. Oliveira, Anders L. Madsen

Proceedings of the Advances in Artificial Intelligence, 2019

2018

A Review of Inference Algorithms for Hybrid Bayesian Networks.

Antonio Salmerón, Rafael Rumí, Helge Langseth, Thomas D. Nielsen, Anders L. Madsen

J. Artif. Intell. Res., 2018

Early and Accurate Recognition of Highway Traffic Maneuvers Considering Real World Application: A Novel Framework Using Bayesian Networks.

Galia Weidl, Anders L. Madsen, Stevens Wang, Dietmar Kasper, Martin Karlsen

IEEE Intell. Transp. Syst. Mag., 2018

Scalable importance sampling estimation of Gaussian mixture posteriors in Bayesian networks.

Darío Ramos-López, Andrés R. Masegosa, Antonio Salmerón, Rafael Rumí, Helge Langseth, Thomas D. Nielsen, Anders L. Madsen

Int. J. Approx. Reason., 2018

An empirical study of Bayesian network inference with simple propagation.

Cory J. Butz, Jhonatan de S. Oliveira, André E. dos Santos, Anders L. Madsen

Int. J. Approx. Reason., 2018

Simple Propagation with Arc-Reversal in Bayesian Networks.

Anders L. Madsen, Cory J. Butz, Jhonatan de S. Oliveira, André E. dos Santos

Proceedings of the International Conference on Probabilistic Graphical Models, 2018

A component framework as an enabler for industrial cyber physical systems.

Luis Neto, Anders L. Madsen, Nicolaj Søndberg-Jeppesen, Ricardo Silva, João Reis, Peter McIntyre, Gil Gonçalves

Proceedings of the IEEE Industrial Cyber-Physical Systems, 2018

2017

MAP inference in dynamic hybrid Bayesian networks.

Darío Ramos-López, Andrés R. Masegosa, Ana M. Martínez, Antonio Salmerón, Thomas D. Nielsen, Helge Langseth, Anders L. Madsen

Prog. Artif. Intell., 2017

A parallel algorithm for Bayesian network structure learning from large data sets.

Anders L. Madsen, Frank Jensen, Antonio Salmerón, Helge Langseth, Thomas D. Nielsen

Knowl. Based Syst., 2017

Scaling up Bayesian variational inference using distributed computing clusters.

Andrés R. Masegosa, Ana M. Martínez, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Darío Ramos-López, Anders L. Madsen

Int. J. Approx. Reason., 2017

Applying Object-Oriented Bayesian Networks for Smart Diagnosis and Health Monitoring at both Component and Factory Level.

Anders L. Madsen, Nicolaj Søndberg-Jeppesen, Mohamed S. Sayed, Michael Peschl, Niels Lohse

Proceedings of the Advances in Artificial Intelligence: From Theory to Practice, 2017

Bayesian Models of Data Streams with Hierarchical Power Priors.

Andrés R. Masegosa, Thomas D. Nielsen, Helge Langseth, Darío Ramos-López, Antonio Salmerón, Anders L. Madsen

Proceedings of the 34th International Conference on Machine Learning, 2017

Parameter Learning Algorithms for Continuous Model Improvement Using Operational Data.

Anders L. Madsen, Nicolaj Søndberg-Jeppesen, Frank Jensen, Mohamed S. Sayed, Ulrich Moser, Luis Neto, João Reis, Niels Lohse

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2017

2016

Improvements to Variable Elimination and Symbolic Probabilistic Inference for evaluating Influence Diagrams.

Rafael Cabañas, Andrés Cano, Manuel Gómez-Olmedo, Anders L. Madsen

Int. J. Approx. Reason., 2016

Bayesian network inference using marginal trees.

Cory J. Butz, Jhonatan de S. Oliveira, Anders L. Madsen

Int. J. Approx. Reason., 2016

Scalable MAP inference in Bayesian networks based on a Map-Reduce approach.

Darío Ramos-López, Antonio Salmerón, Rafael Rumí, Ana M. Martínez, Thomas D. Nielsen, Andrés R. Masegosa, Helge Langseth, Anders L. Madsen

Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

d-VMP: Distributed Variational Message Passing.

Andrés R. Masegosa, Ana M. Martínez, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Darío Ramos-López, Anders L. Madsen

Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

On Bayesian Network Inference with Simple Propagation.

Cory J. Butz, Jhonatan de S. Oliveira, André E. dos Santos, Anders L. Madsen

Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

Financial Data Analysis with PGMs Using AMIDST.

Rafael Cabañas, Ana M. Martínez, Andrés R. Masegosa, Darío Ramos-López, Antonio Salmerón, Thomas D. Nielsen, Helge Langseth, Anders L. Madsen

Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

Parallel Filter-Based Feature Selection Based on Balanced Incomplete Block Designs.

Antonio Salmerón, Anders L. Madsen, Frank Jensen, Helge Langseth, Thomas D. Nielsen, Darío Ramos-López, Ana M. Martínez, Andrés R. Masegosa

Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

On Tree Structures Used by Simple Propagation.

Anders L. Madsen, Cory J. Butz, Jhonatan de S. Oliveira, André E. dos Santos

Proceedings of the Advances in Artificial Intelligence, 2016

2015

Dynamic Bayesian modeling for risk prediction in credit operations.

Hanen Borchani, Ana M. Martínez, Andrés R. Masegosa, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Antonio Fernández, Anders L. Madsen, Ramón Sáez

Proceedings of the Thirteenth Scandinavian Conference on Artificial Intelligence, 2015

SelSus: Towards a reference architecture for diagnostics and predictive maintenance using smart manufacturing devices.

Mohamed S. Sayed, Niels Lohse, Nicolaj Søndberg-Jeppesen, Anders L. Madsen

Proceedings of the 13th IEEE International Conference on Industrial Informatics, 2015

A methodology for developing local smart diagnostic models using expert knowledge.

Anders L. Madsen, Nicolaj Søndberg-Jeppesen, Niels Lohse, Mohamed S. Sayed

Proceedings of the 13th IEEE International Conference on Industrial Informatics, 2015

Modeling Concept Drift: A Probabilistic Graphical Model Based Approach.

Hanen Borchani, Ana M. Martínez, Andrés R. Masegosa, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Antonio Fernández, Anders L. Madsen, Ramón Sáez

Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

Early Recognition of Maneuvers in Highway Traffic.

Galia Weidl, Anders L. Madsen, Viacheslav Tereshchenko, Dietmar Kasper, Gabi Breuel

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2015

MPE Inference in Conditional Linear Gaussian Networks.

Antonio Salmerón, Rafael Rumí, Helge Langseth, Anders L. Madsen, Thomas D. Nielsen

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2015

Parallel Importance Sampling in Conditional Linear Gaussian Networks.

Antonio Salmerón, Darío Ramos-López, Hanen Borchani, Ana M. Martínez, Andrés R. Masegosa, Antonio Fernández, Helge Langseth, Anders L. Madsen, Thomas D. Nielsen

Proceedings of the Advances in Artificial Intelligence, 2015

Parallelisation of the PC Algorithm.

Anders L. Madsen, Frank Jensen, Antonio Salmerón, Helge Langseth, Thomas D. Nielsen

Proceedings of the Advances in Artificial Intelligence, 2015

Exploiting Semantics in Bayesian Network Inference Using Lazy Propagation.

Anders L. Madsen, Cory J. Butz

Proceedings of the Advances in Artificial Intelligence, 2015

2014

A New Method for Vertical Parallelisation of TAN Learning Based on Balanced Incomplete Block Designs.

Anders L. Madsen, Frank Jensen, Antonio Salmerón, Martin Karlsen, Helge Langseth, Thomas D. Nielsen

Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

Bayesian Networks with Function Nodes.

Anders L. Madsen, Frank Jensen, Martin Karlsen, Nicolaj Søndberg-Jeppesen

Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

On SPI-Lazy Evaluation of Influence Diagrams.

Rafael Cabañas, Andrés Cano, Manuel Gómez-Olmedo, Anders L. Madsen

Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

Requirement Engineering for a Small Project with Pre-Specified Scope.

Thomas D. Nielsen, Sigve Hovda, Antonio Fernández, Helge Langseth, Anders L. Madsen, Andrés R. Masegosa, Antonio Salmerón

Proceedings of the 27th Norsk Informatikkonferanse, 2014

On SPI for Evaluating Influence Diagrams.

Rafael Cabañas, Anders L. Madsen, Andrés Cano, Manuel Gómez-Olmedo

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2014

Optimizing Bayesian networks for recognition of driving maneuvers to meet the automotive requirements.

Galia Weidl, Anders L. Madsen, Dietmar Kasper, Gabi Breuel

Proceedings of the 2014 IEEE International Symposium on Intelligent Control, 2014

2013

Ordering arc-reversal operations when eliminating variables in lazy AR propagation.

Anders L. Madsen, Cory J. Butz

Int. J. Approx. Reason., 2013

A Software Package for Web Deployment of Probabilistic Graphical Models.

Anders L. Madsen, Martin Karlsen, Gary C. Barker, Ana Belén García, Jeffrey Hoorfar, Frank Jensen, Håkan Vigre

Proceedings of the Twelfth Scandinavian Conference on Artificial Intelligence, 2013

Heuristics for Determining the Elimination Ordering in the Influence Diagram Evaluation with Binary Trees.

Rafael Cabañas, Andrés Cano, Manuel Gómez-Olmedo, Anders L. Madsen

Proceedings of the Twelfth Scandinavian Conference on Artificial Intelligence, 2013

On the Tree Structure Used by Lazy Propagation for Inference in Bayesian Networks.

Anders L. Madsen, Cory J. Butz

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2013

On Semantics of Inference in Bayesian Networks.

Cory J. Butz, Wen Yan, Anders L. Madsen

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2013

Approximate Lazy Evaluation of Influence Diagrams.

Rafael Cabañas, Andrés Cano, Manuel Gómez-Olmedo, Anders L. Madsen

Proceedings of the Advances in Artificial Intelligence, 2013

d-Separation: Strong Completeness of Semantics in Bayesian Network Inference.

Cory J. Butz, Wen Yan, Anders L. Madsen

Proceedings of the Advances in Artificial Intelligence, 2013

2012

An Empirical Evaluation of Possible Variations of Lazy Propagation

Anders L. Madsen

CoRR, 2012

A Differential Semantics of Lazy AR Propagation

Anders L. Madsen

CoRR, 2012

2011

Using Four Cost Measures to Determine Arc Reversal Orderings.

Cory J. Butz, Anders L. Madsen, Kevin Williams

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2011

2010

Improvements to message computation in lazy propagation.

Anders L. Madsen

Int. J. Approx. Reason., 2010

2008

Belief update in CLG Bayesian networks with lazy propagation.

Anders L. Madsen

Int. J. Approx. Reason., 2008

Integrating Data Sources and Network Analysis Tools to Support the Fight Against Organized Crime.

Luigi Ferrara, Christian Mårtenson, Pontus Svenson, Per Svensson, Justo Hidalgo, Anastasio Molano, Anders L. Madsen

Proceedings of the Intelligence and Security Informatics, 2008

2006

Variations over the message computation algorithm of lazy propagation.

Anders L. Madsen

IEEE Trans. Syst. Man Cybern. Part B, 2006

2005

Solving linear-quadratic conditional Gaussian influence diagrams.

Anders L. Madsen, Frank Jensen

Int. J. Approx. Reason., 2005

The Hugin Tool for Probabilistic Graphical Models.

Anders L. Madsen, Frank Jensen, Uffe Kjærulff, Michael Lang

Int. J. Artif. Intell. Tools, 2005

Applications of object-oriented Bayesian networks for condition monitoring, root cause analysis and decision support on operation of complex continuous processes.

Galia Weidl, Anders L. Madsen, Stefan Israelson

Comput. Chem. Eng., 2005

2003

ADVOCATE II: ADVanced On-Board Diagnosis and Control of Autonomous Systems II.

Miguel Ángel Sotelo, Luis Miguel Bergasa, Ramón Flores, Manuel Ocaña, Marie-Hélène Doussin, Luis Magdalena, Joerg Kalwa, Anders L. Madsen, Michel Perrier, Damien Roland Pietro Corigliano

Proceedings of the Computer Aided Systems Theory, 2003

The Hugin Tool for Learning Bayesian Networks.

Anders L. Madsen, Michael Lang, Uffe Kjærulff, Frank Jensen

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2003

Mixed Influence Diagrams.

Anders L. Madsen, Frank Jensen

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2003

2002

Maximal prime subgraph decomposition of Bayesian networks.

Kristian G. Olesen, Anders L. Madsen

IEEE Trans. Syst. Man Cybern. Part B, 2002

Practical modeling of Bayesian decision problems - exploiting deterministic relations.

Anders L. Madsen, Kristian G. Olesen, Søren L. Dittmer

IEEE Trans. Syst. Man Cybern. Part B, 2002

Hugin - The Tool for Bayesian Networks and Influence Diagrams.

Frank Jensen, Uffe Kjærulff, Michael Lang, Anders L. Madsen

Proceedings of the First European Workshop on Probabilistic Graphical Models, 6-8 November - 2002, 2002

Condition Monitoring, Root Cause Analysis and Decision Support on Urgency of Actions.

Galia Weidl, Anders L. Madsen, Erik Dahlquist

Proceedings of the Soft Computing Systems - Design, Management and Applications, 2002

2001

Solving Influence Diagrams using HUGIN, Shafer-Shenoy and Lazy Propagation.

Anders L. Madsen, Dennis Nilsson

Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

2000

A Factorized Representation of Independence of Causal Influence and Lazy Propagation.

Anders L. Madsen, Bruce D'Ambrosio

Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2000

1999

LAZY Propagation: A Junction Tree Inference Algorithm Based on Lazy Evaluation.

Anders L. Madsen, Finn Verner Jensen

Artif. Intell., 1999

Lazy Evaluation of Symmetric Bayesian Decision Problems.

Anders L. Madsen, Finn Verner Jensen

Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

Lazy Propagation and Independence of Causal Influence.

Anders L. Madsen, Bruce D'Ambrosio

Proceedings of the Symbolic and Quantitative Approaches to Reasoning and Uncertainty, 1999

1998

Lazy Propagation in Junction Trees.

Anders L. Madsen, Finn Verner Jensen

Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

ProbSy--A System for the Calculation of Probabilities in the Card Game Bridge.

Anders L. Madsen, Lars M. Nielsen, Finn Verner Jensen

Proceedings of the Eleventh International Florida Artificial Intelligence Research Society Conference, 1998

Lazy Propagation and Independence of Causal Influence.

Anders L. Madsen

Proceedings of the 13th European Conference on Artificial Intelligence, 1998