Publications

Below, I provide a list of all my publications, ordered by date and organized into different categories. For most of the publications in this list, a downloadable version is available in pdf format. In some cases this is a pre- or postprint version, which is provided here for easy access. It may differ in small details from the actually published version. If you intend to refer to my papers, please get them in their published form.

The library of Ghent University also has a list of my main publications. If you intend to link to my work, please use the links on that page. For individual publications, these links are provided in the list below (http). Most of my main publications are also available on ResearchGate.

To preserve space and avoid cluttering of this list, I have abbreviated the name of Gert de Cooman (GdC) and myself (JDB).

Articles in Journals

  1. Natan T'Joens & JDB. Average Behaviour in Discrete-Time Imprecise Markov Chains: A Study of Weak Ergodicity. International Journal of Approximate Reasoning, 132:181-205. May 2021.
        [ doi ] [ Paper: .pdf ] [ arXiv: 2102.04793 ]
  2. Natan T'Joens, JDB & GdC. A Particular Upper Expectation as Global Belief Model for Discrete-Time Finite-State Uncertain Processes. International Journal of Approximate Reasoning, 131:30-55. April 2021.
        [ doi ] [ Paper: .pdf ] [ arXiv: 2008.03258 ]
  3. Meizhu Li, Shaoguang Huang, JDB, GdC & Aleksandra Pižurica. A Robust Dynamic Classifier Selection Approach for Hyperspectral Images with Imprecise Label Information. Sensors, 20(18):5262. September 2020.
        [ doi ] [ Paper: .pdf ]
  4. Alexander Erreygers, JDB. Bounding inferences for large-scale continuous-time Markov chains: A new approach based on lumping and imprecise Markov chains. International Journal of Approximate Reasoning, 115:96-133. December 2019.
        [ doi ] [ http ] [ Paper: .pdf ] [ Erratum: .pdf ]
  5. Alexander Erreygers, JDB, GdC & Arthur Van Camp. Optimal control of a linear system subject to partially specified input noise. International Journal of Robust and Nonlinear Control, 29(12):3892-3914. April 2019.
        [ doi ] [ http ] [ Paper: .pdf ]
  6. JDB. Independent natural extension for infinite spaces. International Journal of Approximate Reasoning, 104:84–107. January 2019.
        [ doi ] [ http ] [ Paper: .pdf ] [ arXiv: 1805.01139 ]
  7. JDB & GdC. A behavioural justification for using sensitivity analysis in imprecise multinomial processes. Journal of Mathematical Analysis and Applications, 468(1):513–546. December 2018.
        [ doi ] [ http ] [ Paper: .pdf ]
  8. Alexander Erreygers, Cristina Rottondi, Giacomo Verticale & JDB. Imprecise Markov Models for Scalable and Robust Performance Evaluation of Flexi-Grid Spectrum Allocation Policies. IEEE Transactions on Communications, 66(11):5401–5414. November 2018.
        [ doi ] [ http ] [ Paper: .pdf ] [ arXiv: 1801.05700 ]
  9. Thomas Krak, JDB & Arno Siebes. Imprecise continuous-time Markov chains. International Journal of Approximate Reasoning, 88:452–528. September 2017.
        [ doi ] [ http ] [ Paper: .pdf ] [ arXiv: 1611.05796 ]
  10. JDB. Credal networks under epistemic irrelevance. International Journal of Approximate Reasoning, 85:107–138. June 2017. (special issue, invited paper)
        [ doi ] [ http ] [ Paper: .pdf ] [ arXiv: 1701.08661 ]
  11. JDB. The Limit Behaviour of Imprecise Continuous-Time Markov Chains. Journal of Nonlinear Science, 27(1):159–196. February 2017.
        [ doi ] [ http ] [ Paper: .pdf ] [ arXiv: 1602.05478 (preliminary version) ]
  12. Stavros Lopatatzidis, JDB & GdC. Computing lower and upper expected first passage and return times in imprecise birth-death chains. International Journal of Approximate Reasoning, 80:137–173. January 2017.
        [ doi ] [ http ] [ Paper: .pdf ]
  13. GdC, JDB & Stavros Lopatatzidis. Imprecise stochastic processes in discrete time: global models, imprecise Markov chains, and ergodic theorems. International Journal of Approximate Reasoning, 76:18–46. September 2016.
        [ doi ] [ http ] [ Paper: .pdf ] [ arXiv: 1411.4173 (preliminary version) ]
  14. Márcio A. Diniz, JDB & Arthur Van Camp. Characterizing Dirichlet priors. The American Statistician, 70(1):9-17. March 2016.
        [ doi ] [ http ] [ Paper: .pdf ]
  15. Stavros Lopatatzidis, JDB, GdC, Stijn De Vuyst & Joris Walraevens. Robust queueing theory: an initial study using imprecise probabilities. Queueing Systems: Theory and Applications, 82(1):75-101. February 2016.
        [ doi ] [ http ] [ Paper: .pdf ]
  16. JDB, Arthur Van Camp, Márcio A. Diniz & GdC. Representation theorems for partially exchangeable random variables. Fuzzy Sets and Systems, 284:1–30. February 2016.
        [ doi ] [ http ] [ Paper: .pdf ]
  17. JDB & GdC. Conditioning, updating and lower probability zero. International Journal of Approximate Reasoning, 67:1–36. December 2015.
        [ doi ] [ http ] [ Paper: .pdf ] [ Corrigendum: .pdf ]
  18. GdC, JDB & Márcio A. Diniz. Coherent predictive inference under exchangeability with imprecise probabilities. Journal of Artificial Intelligence Research, 52:1-95. January 2015.
        [ doi ] [ http ] [ Paper: .pdf ]
  19. JDB & GdC. Extreme lower previsions. Journal of Mathematical Analysis and Applications, 421(2):1042-1080. January 2015.
        [ doi ] [ http ] [ Paper: .pdf ] [ Corrigendum: .pdf ]
  20. JDB & GdC. Credal networks under epistemic irrelevance: the sets of desirable gambles approach. International Journal of Approximate Reasoning, 56(B):178–207. January 2015. (special issue, invited paper)
        [ doi ] [ http ] [ Paper: .pdf ] [ Corrigendum: .pdf ]
  21. JDB & GdC. An efficient algorithm for estimating state sequences in imprecise hidden Markov models. Journal of Artificial Intelligence Research, 50:189-233. May 2014.
        [ doi ] [ http ] [ Paper: .pdf ] [ arXiv: 1210.1791 (preliminary version) ]

Articles in Conference Proceedings

  1. Arne Decadt, JDB & GdC. Inference with Choice Functions Made Practical. Lecture Notes in Computer Science, vol 12322 (Proceedings of SUM 2020): pp. 113-127. September 2020.
        [ doi ] [ Paper: .pdf ] [ arXiv: 2005.03098 ]
  2. Floris Persiau, JDB & GdC. Computable randomness is about more than probabilities. Lecture Notes in Computer Science, vol 12322 (Proceedings of SUM 2020): pp. 172-186. September 2020.
        [ doi ] [ Paper: .pdf ] [ arXiv: 2005.00471 ]
  3. JDB. Archimedean Choice Functions: an Axiomatic Foundation for Imprecise Decision Making. Communications in Computer and Information Science, Volume 1238 (Proceedings of IPMU 2020, Part II): pp. 195-209. June 2020.
        [ doi ] [ http ] [ Paper: .pdf ] [ Presentation: .pdf ] [ arXiv: 2002.05196 ]
  4. Natan T'Joens & JDB. Limit Behaviour of Upper and Lower Expected Time Averages in Discrete-Time Imprecise Markov Chains. Communications in Computer and Information Science, Volume 1238 (Proceedings of IPMU 2020, Part II): pp. 224-238. June 2020.
        [ doi ] [ http ] [ Paper: .pdf ] [ arXiv: 2002.05661 ]
  5. Natan T'Joens, Thomas Krak, JDB & GdC. A Recursive Algorithm for Computing Inferences in Imprecise Markov Chains. Lecture Notes in Computer Science, Volume 11726 (Proceedings of ECSQARU 2019): pp. 455-465. September 2019.
        [ doi ] [ http ] [ Paper: .pdf ] [ arXiv: 1905.12968 ]
  6. JDB & GdC. Interpreting, Axiomatising and Representing Coherent Choice Functions in Terms of Desirability. Proceedings of Machine Learning Research, Volume 103 (Proceedings of ISIPTA 2019): pp. 125-134. July 2019.
        [ http ] [ Paper: .pdf ] [ Poster: .pdf ] [ Presentation: .pdf ]
        [ arXiv: 1903.00336 (extended version with proofs) ]
  7. Natan T'Joens, JDB & GdC. In Search of a Global Belief Model for Discrete-Time Uncertain Processes. Proceedings of Machine Learning Research, Volume 103 (Proceedings of ISIPTA 2019): pp. 377-385. July 2019.
        [ http ] [ Paper: .pdf ] [ Poster: .pdf ] [ Presentation: .pdf ] [ arXiv: 1701.07295 ]
  8. Alexander Erreygers & JDB. First Steps Towards an Imprecise Poisson Process. Proceedings of Machine Learning Research, Volume 103 (Proceedings of ISIPTA 2019): pp. 175-184. July 2019.
        [ http ] [ Paper: .pdf ] [ Poster: .pdf ] [ Presentation: .pdf ]
        [ arXiv: 1905.05734 (version with proofs) ]
  9. Arne Decadt, GdC & JDB. Monte Carlo Estimation for Imprecise Probabilities: Basic Properties. Proceedings of Machine Learning Research, Volume 103 (Proceedings of ISIPTA 2019): pp. 135-144. July 2019.
        [ http ] [ Paper: .pdf ] [ Poster: .pdf ] [ Presentation: .pdf ]
        [ arXiv: 1905.09301 (version with proofs) ]
  10. Thomas Krak, Natan T'Joens & JDB. Hitting Times and Probabilities for Imprecise Markov Chains. Proceedings of Machine Learning Research, Volume 103 (Proceedings of ISIPTA 2019): pp. 265-275. July 2019.
        [ http ] [ Paper: .pdf ] [ Poster: .pdf ] [ Presentation: .pdf ]
        [ arXiv: 1905.08781 (version with proofs) ]
  11. JDB & GdC. A Desirability-Based Axiomatisation for Coherent Choice Functions. Uncertainty Modelling in Data Science (Proceedings of SMPS 2018): pp. 46-53. September 2018. (best paper award)
        [ http ] [ Paper: .pdf ] [ Presentation: .pdf ] [ arXiv: 1806.01044 ]
  12. Alexander Erreygers & JDB. Computing Inferences for Large-Scale Continuous-Time Markov Chains by Combining Lumping with Imprecision. Uncertainty Modelling in Data Science (Proceedings of SMPS 2018): pp. 78-86. September 2018. (best paper award)
        [ http ] [ Paper: .pdf ] [ arXiv: 1804.01020 ]
  13. Thomas Krak, Alexander Erreygers & JDB. An Imprecise Probabilistic Estimator for the Transition Rate Matrix of a Continuous-Time Markov Chain. Uncertainty Modelling in Data Science (Proceedings of SMPS 2018): pp. 124-132. September 2018.
        [ http ] [ Paper: .pdf ] [ arXiv: 1804.01330 ]
  14. Natan T'Joens, JDB & GdC. Continuity of the Shafer-Vovk-Ville Operator. Uncertainty Modelling in Data Science (Proceedings of SMPS 2018): pp. 200-207. September 2018.
        [ http ] [ Paper: .pdf ] [ arXiv: 1804.01980 ]
  15. Meizhu Li, JDB & GdC. Dynamic Classifier Selection Based on Imprecise Probabilities: a Case Study for the Naive Bayes Classifier. Uncertainty Modelling in Data Science (Proceedings of SMPS 2018): pp. 149-156. September 2018.
        [ http ] [ Paper: .pdf ]
  16. JDB. Independent natural extension for infinite spaces: Williams-coherence to the rescue. Proceedings of Machine Learning Research, Volume 62 (Proceedings of ISIPTA 2017): pp. 121-132. July 2017.
        [ http ] [ Paper: .pdf ] [ Poster: .pdf ] [ Presentation: .pdf ]
        [ arXiv: 1701.07295 ]
  17. GdC & JDB. Computable randomness is inherently imprecise. Proceedings of Machine Learning Research, Volume 62 (Proceedings of ISIPTA 2017): pp. 133-144. July 2017.
        [ http ] [ Paper: .pdf ] [ Poster: .pdf ] [ Presentation: .pdf ] [ arXiv: 1703.00931 ]
  18. Alexander Erreygers & JDB. Imprecise continuous-time Markov chains: efficient computational methods with guaranteed error bounds. Proceedings of Machine Learning Research, Volume 62 (Proceedings of ISIPTA 2017): pp. 145-156. July 2017.
        [ http ] [ Paper: .pdf ] [ Erratum: .pdf ] [ Poster: .pdf ] [ Presentation: .pdf ]
        [ arXiv: 1702.07150 ]
  19. Thomas Krak, JDB & Arno Siebes. Efficient computation of updated lower expectations for imprecise continuous-time hidden Markov chains . Proceedings of Machine Learning Research, Volume 62 (Proceedings of ISIPTA 2017): pp. 193-204. July 2017.
        [ http ] [ Paper: .pdf ] [ Poster: .pdf ] [ Presentation: .pdf ] [ arXiv: 1702.06791 ]
  20. Cristina Rottondi, Alexander Erreygers, Giacomo Verticale & JDB. Modelling spectrum assignment in a two-service flexi-grid optical link with imprecise continuous-time Markov chains. Proceedings of DRCN 2017: pp. 39-46. March 2017. (best paper award)
        [ http ] [ Paper: .pdf ]
  21. JDB. Reintroducing credal networks under epistemic irrelevance. Proceedings of Machine Learning Research, Volume 52 (Proceedings of PGM 2016): pp. 123-135. September 2016.
        [ http ] [ Paper: .pdf ] [ Presentation: .pdf ]
  22. Janneke H. Bolt, JDB & Silja Renooij. Exploiting Bayesian Network Sensitivity Functions for Inference in Credal Networks. Frontiers in Artificial Intelligence and Applications, Volume 285 (Proceedings of ECAI 2016): pp. 646-654. September 2016.
        [ doi ] [ http ] [ Paper: .pdf ]
  23. GdC, JDB & Stavros Lopatatzidis. A pointwise ergodic theorem for imprecise Markov Chains. Proceedings of ISIPTA '15: pp. 107-115. July 2015.
        [ http ] [ Paper: .pdf ] [ Poster: .pdf ] [ Presentation: .pdf ]
  24. Stavros Lopatatzidis, JDB & GdC. Calculating bounds on expected return and first passage times in finite-state imprecise birth-death chains. Proceedings of ISIPTA '15: pp. 177-186. July 2015.
        [ http ] [ Paper: .pdf ] [ Poster: .pdf ] [ Presentation: .pdf ]
  25. JDB, Cassio P. de Campos & Alessandro Antonucci. Global sensitivity analysis for MAP inference in graphical models. Advances in Neural Information Processing Systems 27 (Proceedings of NIPS 2014): pp. 2690- 2698. December 2014.
        http ] [ Paper: .pdf ] [ Supplementary material: .pdf ]
  26. Cedric De Boom, JDB, Arthur Van Camp & GdC. Robustifying the Viterbi algorithm. Lecture Notes in Computer Science, Volume 8754 (Proceedings of PGM 2014): pp. 160-175. September 2014.
        [ doi ] [ http ] [ Paper: .pdf ] [ Presentation: .pdf ]
  27. GdC, JDB & Márcio A. Diniz. Predictive inference under exchangeability, and the Imprecise Dirichlet Multinomial Model. Interdisciplinary Bayesian Statistics (Proceedings of EBEB 2014): pp. 13-33. March 2014.
        [ http ] [ Paper: .pdf ] [ Corrigendum: .pdf ] [ Presentation: .pdf ]
  28. JDB & GdC. Extreme lower previsions and Minkowski indecomposability. Lecture Notes in Computer Science, Volume 7958 (Proceedings of ECSQARU 2013): pp. 157-168. July 2013. (best student paper award)
        [ doi ] [ http ] [ Paper: .pdf ] [ Corrigendum: .pdf ] [ Presentation: .pdf ]
  29. JDB & GdC. Credal networks under epistemic irrelevance using sets of desirable gambles. Proceedings of ISIPTA '13: pp. 99-108. July 2013.
        [ http ] [ Paper: .pdf ] [ Poster: .pdf (poster prize 5th place) ] [ Presentation: .pdf ]
        [ arXiv: 1208.1136 (preliminary version) ]
  30. JDB & GdC. Allowing for probability zero in credal networks under epistemic irrelevance. Proceedings of ISIPTA '13: pp. 109-118. July 2013.
        [ http ] [ Paper: .pdf ] [ Poster: .pdf ] [ Presentation: .pdf ]
  31. GdC, JDB & Arthur Van Camp. Recent advances in imprecise-probabilistic graphical models. Frontiers in Artificial Intelligence and Applications, Volume 242 (Proceedings of ECAI 2012): pp. 27-32. August 2012.
        [ doi ] [ http ] [ Paper: .pdf ]
  32. JDB & GdC. Imprecise Bernoulli processes. Communications in Computer and Information Science, Volume 299 (Proceedings of IPMU 2012): pp. 400-409. July 2012.
        [ doi ] [ http ] [ Paper: .pdf ] [ Presentation: .pdf ]
  33. JDB & GdC. State sequence prediction in imprecise hidden Markov models. Proceedings of ISIPTA '11: pp. 159-168. July 2011.
        [ http ] [ Paper: .pdf ] [ Poster: .pdf (poster prize runner-up) ] [ Presentation: .pdf ]

Posters and Presentations

  1. JDB. What if you don’t know your probabilities? A crash course in imprecise probabilities and their application to Markov chains. Seminar at the School of Mathematical and Physical Sciences of the University of Sussex, England. November 2019.
        [ Abstract: .txt ] [ Presentation: .pdf ]
  2. GdC & JDB. Choice Models: From Linear Option Spaces to Sets Of Horse Lotteries. Poster presentation at ISIPTA 2019. July 2019.
        [ Abstract: .pdf ] [ Poster: .pdf ] [ Presentation: .pdf ]
  3. Thomas Krak & JDB. Computing Expected Hitting Times for Imprecise Markov Chains. Poster presentation at ISIPTA 2019. July 2019.
        [ Abstract: .pdf ] [ Poster: .pdf ]
  4. Thomas Krak, Alexander Erreygers & JDB. An Imprecise Probabilistic Estimator for the Transition Rate Matrix of a Continuous-Time Markov Chain. Presentation at UQOP 2019. March 2019.
        [ Abstract: .pdf ]
  5. JDB & Thomas Krak. Imprecise Markov chains. Invited tutorial at SMPS/BELIEF 2018. September 2018.
        [ Presentation: .pdf ]
  6. GdC & JDB. Imprecise Markov chains: from basic theory to applications. Invited lecture at the UTOPIAE Opening Training School. November 2017.
        [ Abstract: .txt ] [ Presentation GdC: .pdf ] [ Presentation JDB.pdf ]
  7. GdC, JDB & Márcio A. Diniz. Coherent Predictive Inference under Exchangeability with Imprecise Probabilities. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, Journal track: pp. 4995-4999. August 2017.
        [ Extended abstract: .pdf ]
  8. Alexander Erreygers & JDB. Handling the state space explosion of Markov chains: How lumping introduces imprecision (almost) inevitably. Poster presentation at ISIPTA '17. July 2017.
        [ Abstract: .pdf ] [ Poster: .pdf ]
  9. Cristina Rottondi, Alexander Erreygers, Giacomo Verticale & JDB. Modelling spectrum assignment in a two-service flexi-grid optical link with imprecise continuous-time Markov chains. Poster presentation at ISIPTA '17. July 2017.
        [ Abstract: .pdf ] [ Poster: .pdf ]
  10. Natan T'Joens, GdC, JDB & Arthur Van Camp. Active elicitation of imprecise probability models. Poster presentation at ISIPTA '17. July 2017.
        [ Abstract: .pdf ] [ Poster: .pdf ]
  11. Meizhu Li, JDB & GdC. Imprecise classification of the gram status of the causal pathogen of clinical mastitis. Poster presentation at ISIPTA '17. July 2017.
        [ Abstract: .pdf ] [ Poster: .pdf ]
  12. Alexander Erreygers, JDB, GdC & Arthur Van Camp. LQ optimal control for partially specified input noise. Presentation at EURO 2016. July 2016.
        [ Abstract: .pdf ] [ Presentation: .pdf ]
  13. JDB. Convergence of Continuous-Time Imprecise Markov Chains. Poster abstract in proceedings of ISIPTA '15: p. 337. July 2015.
        [ Abstract: .pdf ] [ Poster: .pdf ]
  14. Alexander Erreygers, JDB, GdC & Arthur Van Camp. Optimal control of linear systems with quadratic cost and imprecise forward irrelevant input noise. Poster abstract in proceedings of ISIPTA '15: p. 341. July 2015.
        [ Abstract: .pdf ] [ Poster: .pdf ]
  15. Stavros Lopatatzidis, JDB & GdC. Computational methods for imprecise continuous-time birth-death processes: a preliminary study of flipping times. Poster abstract in proceedings of ISIPTA '15: p. 344. July 2015.
        [ Abstract: .pdf ] [ Poster: .pdf ]
  16. GdC, JDB, Stavros Lopatatzidis. A pointwise ergodic theorem for imprecise Markov chains. Poster at the 15th FEA PhD Symposium. December 2014.
        [ Poster: .pdf ]
  17. JDB. Model uncertainty in Bayesian networks: an imprecise-probabilistic approach. Seminar at the Department of Mathematical Sciences of Durham University, England. December 2014.
        [ Abstract: .txt ]
  18. JDB. Imprecise probability trees: a comparison of two different approaches and their limit behaviour. Presentation at GTP 2014 in Guanajuato, Mexico. November 2014.
        [ Abstract: .txt ]
  19. JDB. Credal networks under epistemic irrelevance. Presentation at WPMSIIP 2014 in Gent, Belgium. September 2014.
        [ Presentation: .pdf ]
  20. Stavros Lopatatzidis, JDB, GdC, Stijn De Vuyst, Joris Walraevens. Robustness in queueing systems. Presentation at ECQT 2014 in Gent, Belgium. September 2014.
        [ Abstract: .pdf ] [ Presentation: .pdf ]
  21. Márcio A. Diniz, JDB & Arthur Van Camp. Characterising Dirichlet Priors. Presentation at the 12th Brazilian Meeting on Bayesian Statistics in Atibaia, Brazil. March 2014.
        [ Abstract: .pdf ] [ Presentation: .pdf ]
  22. JDB. Decision making in credal networks. Presentation at WPMSIIP 2013 in Lugano, Switzerland. September 2013.
        [ Presentation: .pdf ]
  23. JDB. Credal networks under epistemic irrelevance. Presentation at WPMSIIP 2013 in Lugano, Switzerland. September 2013.
        [ Presentation: .pdf ]
  24. Stavros Lopatatzidis, JDB & GdC. First steps towards Little’s Law with imprecise probabilities. Poster abstract in proceedings of ISIPTA '13: pp. 392-393. July 2013.
        [ Abstract: .pdf ] [ Poster: .pdf ]
  25. JDB. Credal networks: an overview of different approaches. Presentation at UUvUG workshop. June 2013.
        [ Presentation: .pdf ]
  26. JDB. Imprecise multinomial processes: an overview of different approaches and how they are related to each other. Presentation at the Fourth Workshop on Game-Theoretic Probability and Related Topics in Tokyo, Japan. November 2012.
        [ Abstract: .txt ] [ Presentation: .pdf ]
  27. JDB. Robustly correcting mistakes made by OCR software. Lecture at the 5th SIPTA Summer School in Pescara, Italy. July 2012.
        [ Presentation: .pdf ]
  28. JDB. State sequence estimation in imprecise hidden Markov models. Lecture at the 5th SIPTA Summer School in Pescara, Italy. July 2012.
        [ Presentation: .pdf ]
  29. JDB. Imprecise Bernoulli processes. Presentation at SYSTeMS Dialogue. April 2012.
        [ Abstract: .txt ] [ Presentation: .pdf ]
  30. JDB. Imprecise Bernoulli processes. Presentation at WaFT workshop on Decision Making, Imprecise- and Game theoretical probabilities. April 2012.
        [ Abstract: .txt ] [ Presentation: .pdf ]
  31. JDB. State sequence prediction in imprecise hidden Markov models. Poster at the 12th FEA PhD Symposium. December 2011.
        [ Popular scientific text: .pdf ] [ Poster: .pdf ]
  32. JDB. EstiHMM: een efficiënt algoritme ter bepaling van de maximale sequenties in een imprecies hidden Markovmodel. Poster at ie-prijzen 2011. December 2011.
        [ Poster: .pdf (dutch) ]
  33. JDB. State sequence prediction in imprecise hidden Markov models. Presentation at BENE@WORK. December 2011.
        [ Abstract: .txt ] [ Presentation: .pdf ]
  34. JDB & GdC. State sequence prediction in imprecise hidden Markov models. Poster at DYSCO Study Day Program & Abstracts: p. 11. November 2011.
        [ Abstract: .txt ] [ Poster: .pdf ]
  35. Arthur Van Camp, GdC, JDB, Erik Quaeghebeur & Filip Hermans. Learning Imprecise Hidden Markov Models. Poster at ISIPTA '11 Program & Abstracts: p. 34. July 2011.
        [ Abstract: .pdf ] [ Poster: .pdf ]
  36. JDB. State sequence prediction in imprecise hidden Markov models. Informal Presentation at IDSIA. November 2010.
        [ Presentation: .pdf ]

Publications as Editor

  1. JDB, GdC, Cassio P. de Campos, Erik Quaeghebeur & Gregory Wheeler, editors. Proceedings of Machine Learning Research, Volume 103 (Proceedings of ISIPTA 2019) Ghent, Belgium, July 2019.
        [ http ] [ Proceedings: website ] [ Preface: .pdf ]

PhD and Master thesis

  1. JDB. Credal Networks under Epistemic Irrelevance: Theory and Algorithms (Credale netwerken onder epistemische irrelevantie: theorie en algoritmen). PhD Thesis at Ghent University. Supervised by GdC. May 2015.
        [ http ] [ Thesis: .pdf ] [ Corrigendum: .pdf ] [ Presentation: .pdf ]
  2. JDB. EstiHMM: een efficiënt algoritme ter bepaling van de maximale sequenties in een imprecies hidden Markovmodel. Master Thesis at Ghent University. Supervised by GdC. June 2011.
        [ Thesis: .pdf (dutch) ] [ Extended Abstract: .pdf ] [ Presentation: .pdf (dutch) ]

Technical reports

  1. JDB. Axiom E6 is needed in Proposition 6.9 of "Game-Theoretic Foundations for Probability and Finance". December 2020.
        [ Counterexample: .pdf ]
  2. Natan T'Joens, JDB & GdC. Continuity Properties of Game-theoretic Upper Expectations. February 2019.
        [ arXiv: 1902.09406 ]
  3. JDB & GdC. Continuity of imprecise stochastic processes with respect to the pointwise convergence of monotone sequences. February 2014.
        [ arXiv: 1402.3056 ]

Work in progress (tentative titles)

  1. Natan T'Joens, JDB & GdC. Game-Theoretic Upper Expectations for Discrete-Time Finite-State Uncertain Processes.
        [ arXiv: 2008.03133 ]
  2. JDB & GdC. On a notion of independence proposed by Teddy Seidenfeld.
        [ arXiv: 2102.10342 ]
  3. GdC & JDB. Randomness is inherently imprecise.
        [ Paper: .pdf ]
  4. JDB & Natan T'Joens. A Pointwise Ergodic Theorem for Lower Expected Time Averages.
  5. Natan T'Joens & JDB. Global Upper Expectations for Discrete-Time Stochastic Processes: In Practice, They Are All The Same!.
        [ arXiv: 2102.13075 ]
  6. Alexander Erreygers & JDB. Extending the Domain of Imprecise Jump Processes From Simple Variables to Measurable Ones.
  7. GdC & JDB. Randomness and Imprecision: A Discussion of Recent Results.
        [ Paper: .pdf ]
  8. Floris Persiau, JDB & GdC. A Remarkable Equivalence between Non-Stationary Precise and Stationary Imprecise Uncertainty Models in Computable Randomness.
        [ Paper: .pdf ]
  9. JDB, Alexander Erreygers & Thomas Krak. Sum-Product Laws and Efficient Algorithms for Imprecise Markov Chains.
  10. JDB. Choice functions based on sets of strict partial orders: an axiomatic characterisation.
        [ arXiv: 2003.11631 ]
  11. Jean-Charles Croix, JDB & István Zoltán Kiss. Bounding the prevalence of epidemics on networks: an imprecise perspective.
  12. Matthias C. M. Troffaes, Damjan Škulj & JDB. Model checking for imprecise Markov chains.
  13. JDB. Efficient inference algorithms for credal networks under epistemic irrelevance.