Billede af Thomas Dyhre Nielsen

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Thomas Dyhre Nielsen

 https://orcid.org/0000-0002-4823-6341

  • Selma Lagerløfs Vej 300, 1-2-03

    9220 Aalborg Ø

    Danmark

1997 …2024

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  • 2024

    Compositional Control Synthesis for Water Management System

    Kim, E. H., Larsen, K. G., Nielsen, T. D. & Goorden, M., 28 feb. 2024, (Accepteret/In press) ECC. s. 1-8 8 s.

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  • 2023

    Graph Neural Networks for Metagenomic Binning

    Lamurias, A., Tibo, A., Hose, K., Albertsen, M. & Nielsen, T. D., 2023, The 2023 ICML Workshop on Computational Biology. 7 s. 81

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  • Guaranteed safe controller synthesis for switched systems using analytical solutions

    Goorden, M., Larsen, K. G., Nielsen, J. E., Nielsen, T. D., Qian, W., Rasmussen, M. R. & Zhao, G., 2023, 2023 IEEE Conference on Control Technology and Applications, CCTA 2023. IEEE, s. 784-790 7 s. (IEEE Conference on Control Technology and Applications (CCTA) - Proceedings).

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  • Metagenomic Binning using Connectivity-constrained Variational Autoencoders

    Lamurias, A., Tibo, A., Hose, K., Nielsen, T. D. & Albertsen, M., 2023, Proceedings of the 40th International Conference on Machine Learning. Krause, A. & Brunskill, E. (red.). s. 18471–18481 762. (The Proceedings of Machine Learning Research, Bind 202).

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  • Patient Event Sequences for Predicting Hospitalization Length of Stay

    Hansen, E. R., Nielsen, T. D., Larsen, T. M., Strausholm, M. N., Sagi, T. & Hose, K., 7 jun. 2023, Artificial Intelligence in Medicine: 21st International Conference on Artificial Intelligence in Medicine, AIME 2023, Portorož, Slovenia, June 12–15, 2023, Proceedings. Juarez, J. M., Marcos, M., Stiglic, G. & Tucker, A. (red.). Springer, s. 51-56 6 s. (Lecture Notes in Computer Science (LNCS), Bind LNCS 13897).

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  • 2022

    A Reparameterization of Mixtures of Truncated Basis Functions and its Applications

    Salmerón, A., Langseth, H., Masegosa, A. & Nielsen, T. D., 2022, Proceedings of the 11th International Conference on Probabilistic Graphical Models : PMLR. Salmerón, A. & Rumı́, R. (red.). PMLR Press, Bind 186. s. 205-216 (The Proceedings of Machine Learning Research, Bind 186).

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  • Controlling Stormwater Detention Ponds under Partial Observability

    Kim, E. H., Nielsen, T. D., Larsen, K. G. & Goorden, M., 2 nov. 2022, NWPT: 33rd Nordic Workshop on Programming Theory. Nordic Workshop on Programming Theory, s. 1-3 3 s.

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  • 2021

    Learning Safe and Optimal Control Strategies for Storm Water Detention Ponds

    Goorden, M., Larsen, K. G., Nielsen, J. E., Nielsen, T. D., Rasmussen, M. R. & Srba, J., 2021, IFAC-PapersOnLine: 7th IFAC Conference on Analysis and Design of Hybrid Systems. 5 udg. Elsevier, Bind 54. s. 13-18 6 s. (IFAC-PapersOnLine; Nr. 5, Bind 54).

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    8 Citationer (Scopus)
    98 Downloads (Pure)

  • SolveDB+: SQL-based prescriptive analytics

    Siksnys, L., Pedersen, T. B., Nielsen, T. D. & Frazzetto, D., 2021, Advances in Database Technology - EDBT 2021: 24th International Conference on Extending Database Technology, Proceedings. Velegrakis, Y., Zeinalipour, D., Chrysanthis, P. K. & Guerra, F. (red.). OpenProceedings.org, s. 133-144 12 s. (Advances in Database Technology).

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    1 Citationer (Scopus)
    134 Downloads (Pure)
  • 2019

    Graph Convolutional Networks for Road Networks

    Skovgaard Jepsen, T., Jensen, C. S. & Nielsen, T. D., 5 nov. 2019, Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Banaei-Kashani, F., Trajcevski, G., Guting, R. H., Kulik, L. & Newsam, S. (red.). Association for Computing Machinery, s. 460-463 4 s.

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    27 Citationer (Scopus)
    379 Downloads (Pure)
  • 2018

    Adaptive User-Oriented Direct Load-Control of Residential Flexible Devices

    Frazzetto, D., Neupane, B., Pedersen, T. B. & Nielsen, T. D., 12 jun. 2018, e-Energy 2018 - Proceedings of the 9th ACM International Conference on Future Energy Systems. Association for Computing Machinery, s. 1-11 11 s.

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    10 Citationer (Scopus)

  • On Network Embedding for Machine Learning on Road Networks: A Case Study on the Danish Road Network

    Jepsen, T. S., Jensen, C. S., Nielsen, T. D. & Torp, K., 2018, Proceedings of the 2018 IEEE International Conference on Big Data. IEEE, s. 3421-3430 10 s.

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    12 Citationer (Scopus)
  • 2017

    Bayesian models of data streams with Hierarchical Power Priors

    Masegosa, A., Nielsen, T. D., Langseth, H., Ramos-López, D., Salmerón, A. & Madsen, A. L., 2017, Proceedings of the 34th International Conference on Machine Learning. Bind 70. s. 2334-2343

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    5 Citationer (Scopus)

  • Financial Data Analysis with PGMs Using AMIDST

    Cabanas, R., Martinez, A. M., Masegosa, A. R., Ramos-Lopez, D., Sameron, A., Nielsen, T. D., Langseth, H. & Madsen, A. L., 30 jan. 2017, Proceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016. IEEE, s. 1284-1287 4 s. 7836816

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    4 Citationer (Scopus)
  • 2016

    d-VMP: Distributed Variational Message Passing

    Masegosa, A., Martinez, A. M., Langseth, H., Nielsen, T. D., Salmerón, A., Ramos-López, D. & Madsen, A. L., 2016, JMLR Workshop and Conference Proceedings: Volume 52: Proceedings of the Eighth International Conference on Probabilistic Graphical Models. s. 321-332 12 s. (JMLR Workshop and Conference Proceedings, Bind 52).

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    11 Citationer (Scopus)

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

    Salmerón, A., Madsen, A. L., Jensen, F., Langseth, H., Nielsen, T. D., Ramos-López, D., Martinez, A. M. & Masegosa, A., 2016, ECAI 2016: 22nd European Conference on Artificial Intelligence. IOS Press, s. 743-750 8 s. (Frontiers in Artificial Intelligence and Applications, Bind 285).

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    1 Citationer (Scopus)

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

    Ramos-López, D., Salmerón, A., Rumí, R., Martinez, A. M., Nielsen, T. D., Masegosa, A., Langseth, H. & Madsen, A. L., 2016, JMLR Workshop and Conference Proceedings: Volume 52: Proceedings of the Eighth International Conference on Probabilistic Graphical Models. s. 415-425 12 s. (JMLR Workshop and Conference Proceedings, Bind 52).

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  • 2015

    AMIDST: Analysis of MassIve Data STreams

    Masegosa, A., Martinez, A. M., Borchani, H., Ramos-López, D., Nielsen, T. D., Langseth, H., Salmerón, A. & Madsen, A. L., okt. 2015, The 27th Benelux Conference on Artificial Intelligence (BNAIC 2015).

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  • Dynamic Bayesian modeling for risk prediction in credit operations

    Borchani, H., Martinez, A. M., Masegosa, A., Langseth, H., Nielsen, T. D., Salmerón, A., Fernández, A., Madsen, A. L. & Sáez, R., 2015, The 13th Scandinavian Conference on Artificial Intelligence (SCAI'2015). IOS Press, s. 17-26 (Frontiers in Artificial Intelligence and Applications, Bind 278).

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    4 Citationer (Scopus)
    325 Downloads (Pure)

  • Modeling concept drift: A probabilistic graphical model based approach

    Borchani, H., Martinez, A. M., Masegosa, A. R., Langseth, H., Nielsen, T. D., Salmerón, A., Fernández, A., Madsen, A. L. & Sáez, R., 2015, Advances in Intelligent Data Analysis XIV: 14th International Symposium, IDA 2015, Saint Etienne. France, October 22 -24, 2015. Proceedings. Fromont, E., De Bie, T. & van Leeuwen, M. (red.). Springer, s. 72-83 (Lecture Notes in Computer Science; Nr. 9385).

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    17 Citationer (Scopus)
    727 Downloads (Pure)

  • MPE inference in conditional linear gaussian networks

    Salmerón, A., Rumí, R., Langseth, H., Madsen, A. L. & Nielsen, T. D., 2015, Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 13th European Conference, ECSQARU 2015, Compiègne, France, July 15-17, 2015. Proceedings. Destercke, S. & Denoeux, T. (red.). Springer, s. 407-416 (Lecture Notes in Computer Science; Nr. 9161).

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    4 Citationer (Scopus)
    511 Downloads (Pure)

  • Parallel importance sampling in conditional linear Gaussian networks

    Salmerón, A., Ramos-López, D., Borchani, H., Martinez, A. M., Masegosa, A. R., Fernández, A., Langseth, H., Madsen, A. L. & Nielsen, T. D., 2015, Advances in Artificial Intelligence: 16th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2015 Albacete, Spain, November 9–12, 2015 Proceedings. Puerta, J. M., Gámez, J. A., Dorronsoro, B., Barrenechea, E., Troncoso, A., Baruque, B. & Galar, M. (red.). Springer, s. 36-46 (Lecture Notes in Computer Science; Nr. 9422).

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    7 Citationer (Scopus)
    486 Downloads (Pure)

  • Parallelisation of the PC Algorithm

    Madsen, A. L., Jensen, F., Salmerón, A., Langseth, H. & Nielsen, T. D., 2015, Advances in Artificial Intelligence: 16th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2015 Albacete, Spain, November 9–12, 2015 Proceedings. Springer, s. 14-24 11 s. (Lecture Notes in Computer Science, Bind 9422).

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    8 Citationer (Scopus)
    322 Downloads (Pure)
  • 2014

    A new method for vertical parallelisation of TAN learning based on balanced incomplete block designs

    Madsen, A. L., Jensen, F., Salmerón, A., Karlsen, M., Langseth, H. & Nielsen, T. D., 2014, Proceedings of the 7th European Workshop on Probabilistic Graphical Models. Springer Publishing Company, Bind 8754. s. 302-317 16 s. (Lecture Notes in Computer Science).

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    11 Citationer (Scopus)

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

    Nielsen, T. D., Hovda, S., Antontio, F., Langseth, H., Madsen, A. L., Masegosa, A. & Salmerón, A., 2014, NIK: Norsk Informatikkonferanse . 12 s.

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  • 2013

    Learning Mixtures of Polynomials of Conditional Densities from Data

    L. López-Cruz, P., Nielsen, T. D., Bielza, C. & Larrañga, P., 2013, Advances in Artificial Intelligence: 15th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2013, Madrid, Spain, September 17-20, 2013. Proceedings. Bielza et al., C. (red.). Springer Publishing Company, s. 363-372 10 s. (Lecture Notes in Artificial Intelligence : Subseries of Lecture Notes in Computer Science; Nr. XVIII, Bind 8109).

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    1 Citationer (Scopus)
    464 Downloads (Pure)
  • 2012

    Active Learning of Markov Decision Processes for System Verification

    Chen, Y. & Nielsen, T. D., 12 dec. 2012, International Conference on Machine Learning and Applications (ICMLA). s. 289-294

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    19 Citationer (Scopus)
    666 Downloads (Pure)

  • Learning Markov models for stationary system behaviors

    Chen, Y., Mao, H., Jaeger, M., Nielsen, T. D., Larsen, K. G. & Nielsen, B., 2012, NASA Formal Methods: 4th International Symposium, NFM 2012, Norfolk, VA, USA, April 3-5, 2012. Proceedings. Goodloe, A. E. & Person, S. (red.). Springer, s. 216-230 15 s. (Lecture Notes in Computer Science, Bind 7226).

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    13 Citationer (Scopus)
    553 Downloads (Pure)
  • 2011

    Learning Probabilistic Automata for Model Checking

    Mao, H., Chen, Y., Jaeger, M., Nielsen, T. D., Larsen, K. G. & Nielsen, B., 2011, 8th International Conference on Quantitative Evaluation of Systems (QEST). IEEE, s. 111-120 10 s.

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    42 Citationer (Scopus)
    958 Downloads (Pure)
  • 2010

    Towards a more expressive model for dynamic classification

    Zhong, S., Martínez, A. M., Nielsen, T. D. & Langseth, H., 2010, Proceedings of the 23rd International Florida Artificial Intelligence Research Society Conference, FLAIRS-23. AAAI Press, s. 563-564

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    3 Citationer (Scopus)
  • 2008

    An anytime algorithm for evaluating unconstrained influence diagrams

    Luque, M., Nielsen, T. D. & Jensen, F. V., 2008, Proceedings of the Fourth European Workshop on Probabilistic Graphical Models. Jaeger, M. & Nielsen, T. D. (red.). s. 177-184 8 s.

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    5 Citationer (Scopus)
    445 Downloads (Pure)

  • Parameter estimation in mixtures of truncated exponentials

    Langseth, H., Nielsen, T. D., Rumí, R. & Salmerón, A., 2008, Proceedings of the Fourth European Workshop on Probabilistic Graphical Models. Jaeger, M. & Nielsen, T. D. (red.). s. 169-176 8 s.

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    3 Citationer (Scopus)
    125 Downloads (Pure)

  • Robust classification using mixtures of dependency networks

    Gámez, J. A., Mateo, J. L., Nielsen, T. D. & Puerta, J. M., 2008, Proceedings of the Fourth European Workshop on Probabilistic Graphical Models. s. 129-136 8 s.

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    2 Citationer (Scopus)
    214 Downloads (Pure)
  • 2006

    A COTS Framework for Sensor Fusion Using Dynamic Bayesian Networks in Livestock Production

    Hansen, J. A., Nielsen, T. D. & Schiøler, H., 2006, Computer Applications in Industry and Engineering (CAINE-2006), 19th Int'l. Conference. Philip, T. (red.). Denmark., s. 41-48 7 s.

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  • Adapting Bayes Network Structures to Non-stationary Domains

    Nielsen, S. H. & Nielsen, T. D., 2006, Proceedings of the Third European Workshop on Probabilistic Graphical Models. s. 223-230 8 s.

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    6 Citationer (Scopus)

  • Sensor Fusion using Dynamic Bayesian Networks in Livestock Production Buildings

    Hansen, J. A., Nielsen, T. D. & Schiøler, H., 2006, Int. Conf. on Computational Intelligence for Modelling Control and Automation, CIMCA'06. Mohammadian, M. (red.). IEEE Computer Society Press, 7 s.

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    2 Citationer (Scopus)
  • 2005

    Alert Systems for production Plants: A Methodology Based on Conflict Analysis

    Nielsen, T. D. & Jensen, F. V., 2005, Proceedings of the Eighth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty. IEEE Computer Society Press, s. 76-87 (Lecture Notes in Computer Science; Nr. 3571).

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    6 Citationer (Scopus)
    754 Downloads (Pure)
  • 2004

    Multi-currency Influence Diagrams

    Nielsen, S. H., Nielsen, T. D. & Jensen, F. V., 2004, Proceedings of the Second European Workshop on Probabilistic Graphical Models. Lucas, P. (red.). s. 153-160 8 s.

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  • Sequential influence diagrams: a unified asymmetry framework

    Jensen, F. V., Nielsen, T. D. & Shenoy, P., 2004, Proceedings of the second European Workshop on Probabilistic Graphical Models.

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  • 2001

    Cutting Influence Diagrams Down to the Core

    Nielsen, T. D. & Jensen, F. V., 2001, Seventh Scandinavian Conference on Artificial Intelligence : SCAI'01: Frontiers in Artificial Intelligence and Applications. Lund, H. H. : Mayoh, B. : Perram, J. (eds.) (red.). Vol. 66 udg. IOS Press, s. 159-160

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  • Decomposition of Influence Diagrams

    Nielsen, T. D., 2001, Symbolic and Quantitative Approaches to Reasoning with Uncertainty : 6th European Conference, ECSQARU 2001 Toulouse, France, September 19 - 21, 2001 : Proceedings: Lecture Notes in Artificial Intelligence , subseries of Lecture Notes in Computer Science. Benferhat, S. : Besnard, P. (eds.) (red.). 2143 udg. IEEE Computer Society Press, s. 144-155

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    7 Citationer (Scopus)

  • Structural Learning in Object Oriented Domains

    Bangsø, O., Langseth, H. & Nielsen, T. D., 2001, Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS), Key West. s. 340-344

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  • 2000

    Representing and Solving Asymmetric Bayesian Decision Problems

    Nielsen, T. D. & Jensen, F. V., 2000, Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence. Boutilier, C. : Goldszmidt, M. (eds.) (red.). Morgan Kaufmann, s. 416-425

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  • Using ROBDDs for Inference in Bayesian Networks with Troubleshooting as an Example

    Nielsen, T. D., Wuillemin, P-H., Jensen, F. V. & Kjærulff, U. B., 2000, Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence: UAI '00. Boutilier, C. : Goldszmidt, M. (eds.) (red.). Morgan Kaufmann, s. 426-435

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  • 1999

    Well-Defined Decision Scenarios

    Nielsen, T. D. & Jensen, F. V., 1999, Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence. Laskey, K. B. : Prade, H. (eds.) (red.). Morgan Kaufmann, s. 502-511

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