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Peter J.F. Lucas

prof.dr.

 https://orcid.org/0000-0001-5454-2428
Calculated based on number of publications stored in Pure and citations from Scopus
1989 …2022

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  • 2020

    Temporal exceptional model mining using dynamic Bayesian networks

    Bueno, M. L. P., Hommersom, A. & Lucas, P. J. F., 2020, Advanced Analytics and Learning on Temporal Data - 5th ECML PKDD Workshop, AALTD 2020, Revised Selected Papers. Lemaire, V., Malinowski, S., Bagnall, A., Guyet, T., Tavenard, R. & Ifrim, G. (eds.). Springer, p. 97-112 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12588 LNAI).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File
    2 Citations (Scopus)
    8 Downloads (Pure)
  • 2019

    A Data-Driven Exploration of Hypotheses on Disease Dynamics

    Bueno, M. L. P., Hommersom, A., Lucas, P. J. F. & Janzing, J., 2019, Artificial Intelligence in Medicine: 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Poznan, Poland, June 26–29, 2019, Proceedings. Cham: Springer, p. 170-179 (Lecture Notes in Computer Science; vol. 11526).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • 2018

    An improved diagnostic method for probabilistic consistency-based diagnosis

    de Paula Bueno, M. L., Hommersom, A. & Lucas, P., 2018, 28th International Workshop on Principles of Diagnosis (DX '17). Zanella, M., Pill, I. & Cimatti, A. (eds.). EasyChair, Vol. 4. p. 65-77 13 p. (Kalpa Publications in Computing).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File

  • Making continuous time Bayesian networks more flexible

    Liu, M., Stella, F., Hommersom, A. & Lucas, P. J. F., 2018, Proceedings of the Ninth International Conference on Probabilistic Graphical Models: 11-14 September 2018, Prague, Czech Republic. Kratochvíl, V. & Studený, M. (eds.). MLResearchPress, p. 237-248 12 p. (Proceedings of Machine Learning Research (PMLR); vol. 72).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File

  • Modeling the dynamics of multiple disease occurrence by latent states

    Bueno, M. L. P., Hommersom, A., Lucas, P. J. F., Lobo, M. & Rodrigues, P. P., 2018, Scalable Uncertainty Management : 12th International Conference, SUM 2018, Milan, Italy, October 3-5, 2018, Proceedings. Ciucci, D., Pasi, G. & Vantaggi, B. (eds.). Cham: Springer, p. 93-107 15 p. (Lecture Notes in Computer Science; vol. 11142).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    3 Citations (Scopus)

  • Parallel probabilistic inference by weighted model counting

    Dal, G. H., Laarman, A. W. & Lucas, P. J. F., 2018, Proceedings of the Ninth International Conference on Probabilistic Graphical Models: 11-14 September 2018, Prague, Czech Republic. Kratochvíl, V. & Studený, M. (eds.). MLResearchPress, p. 97-108 12 p. (Proceedings of Machine Learning Research (PMLR); vol. 72).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File

  • Representing hypoexponential distributions in continuous time Bayesian networks

    Liu, M., Stella, F., Hommersom, A. & Lucas, P. J. F., 2018, Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications: 17th International Conference, IPMU 2018, Cádiz, Spain, June 11-15, 2018, Proceedings, Part III. Perfilieva, I., Medina, J., Ojeda-Aciego, M., Yager, R. R., Verdegay, J. L. & Bouchon-Meunier, B. (eds.). Cham: Springer, p. 565-577 13 p. (Communications in Computer and Information Science; vol. 855).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • 2017

    Reducing the cost of probabilistic knowledge compilation

    Dal, G., Michels, S. & Lucas, P. J. F., 2017, Proceedings of Machine Learning Research: Advanced Methodologies for Bayesian Networks, 20-22 September 2017. Vol. 73. p. 141-152 12 p.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File
    3 Downloads (Pure)
  • 2016

    Approximate probabilistic inference with bounded error for hybrid probabilistic logic programming

    Michels, S., Hommersom, A. & Lucas, P. J. F., 2016, IJCAI'16: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Brewka, G. (ed.). New York, NY: AAAI Press, p. 3616-3622 7 p. (IJCAI International Joint Conference on Artificial Intelligence; vol. 2016, no. 25).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    6 Citations (Scopus)

  • Learning complex uncertain states changes via asymmetric hidden Markov models: an industrial case

    Bueno, M. L. P., Hommersom, A., Lucas, P. J. F., Verwer, S. & Linard, A., 2016, Conference on Probabilistic Graphical Models, 6-9 September 2016, Lugano, Switzerland. Antonucci, A., Corani, G. & Polpo Campos, C. (eds.). MLResearchPress, p. 50–61 (Proceedings of Machine Learning Research (PMLR); vol. 52).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File

  • Learning parameters of hybrid time Bayesian networks

    Liu, M., Hommersom, A., Hommersom, A., van der Heijden, M. & Lucas, P. J. F., 2016, Conference on Probabilistic Graphical Models, 6-9 September 2016, Lugano, Switzerland. Antonucci, A., Corani, G. & Polpo Campos, C. (eds.). MLResearchPress, p. 287-298 12 p. (Proceedings of Machine Learning Research (PMLR); vol. 52).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File
  • 2014

    Imprecise probabilistic horn clause logic

    Michels, S., Hommersom, A., Lucas, P. J. F. & Velikova, M., 2014, ECAI 2014: 21st European Conference on Artificial Intelligence, 18-24 August 2014, Prague, Czech Republic. Schaub, T., Friedrich, G. & O'Sullivan, B. (eds.). IOS Press, p. 621-626 6 p. (Frontiers in Artificial Intelligence and Applications; vol. 263).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File
    1 Citation (Scopus)
  • 2013

    MoSHCA - My mobile and smart health care assistant

    Hommersom, A., Lucas, P. J. F., Velikova, M., Dal, G., Bastos, J., Rodriguez, J., Germs, M. & Schwietert, H., 2013, 2013 IEEE 15th International Conference on e-Health Networking, Applications and Services, Healthcom 2013. Piscataway, NJ: IEEE, p. 188-192 5 p. 6720664

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    26 Citations (Scopus)

  • Understanding the co-occurrence of diseases using structure learning

    Lappenschaar, M., Hommersom, A., Lagro, J. & Lucas, P. J. F., 2013, Artificial Intelligence in Medicine: 14th Conference on Artificial Intelligence in Medicine, AIME 2013, Murcia, Spain, May 29 -- June 1, 2013, Proceedings. Peek, N., Marín Morales, R. & Peleg, M. (eds.). Berlin, Heidelberg: Springer, p. 135-144 10 p. (Lecture Notes in Computer Science; vol. 7885)(Lecture Notes in Artificial Intelligence).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    10 Citations (Scopus)
  • 2012

    A framework for development, teaching and deployment of inference algorithms

    Evers, S. & Lucas, P. J. F., 2012, Proceedings of the 6th European Workshop on Probabilistic Graphical Models, PGM'12: Granada, Spain, September 19-21, 2012. Nielsen, T. D., Cano, A. & Gomez-Olmedo, M. (eds.). Granada: University of Granada, p. 99-106 8 p.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File

  • A Semi-Causal Bayesian Network Approach to Prognosis

    Hommersom, A., Lucas, P. J. F., van Altena, A. M., Massuger, L. F. A. G. & Kiemeney, L. A., 2012, Proceedings of the 29th International Conference on Machine Learning, Edingburgh, Scotland, June 26-July 1, 2012. Langford, J. (ed.). OmniPress, 8 p.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File
  • 2011

    A predictive Bayesian network model for home management of preeclampsia

    Velikova, M., Lucas, P. J. F. & Spaanderman, M., 2011, Artificial Intelligence in Medicine: 13th Conference on Artificial Intelligence in Medicine, AIME 2011, Bled, Slovenia, July 2-6, 2011, Proceedings. Peleg, M., Lavrač, N. & Combi, C. (eds.). Berlin, Heidelberg: Springer, p. 179-183 5 p. (Lecture Notes in Computer Science; vol. 6747).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    4 Citations (Scopus)