Ghent University Academic Bibliography

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Extending the domain of imprecise jump processes from simple variables to measurable ones

Alexander Erreygers (UGent) and Jasper De Bock (UGent)

(2021) PROCEEDINGS OF MACHINE LEARNING RESEARCH. 147. p.140-149
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In search of a global belief model for discrete-time uncertain processes

Natan T'Joens (UGent) , Jasper De Bock (UGent) and Gert De Cooman (UGent)

(2019) Proceedings of the Eleventh International Symposium on Imprecise Probabilities : Theories and Applications, ISIPTA 2019. In Proceedings of Machine Learning Research 103. p.377-385
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Hitting times and probabilities for imprecise Markov chains

Thomas Krak (UGent) , Natan T'Joens (UGent) and Jasper De Bock (UGent)

(2019) International Symposium on Imprecise Probabilities : Theories and Applications, ISIPTA 2019, Proceedings. In Proceedings of Machine Learning Research 103. p.265-275
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Two-state imprecise Markov chains for statistical modelling of two-state non-Markovian processes

Matthias Troffaes, Thomas Krak (UGent) and Henna Bains

(2019) Proceedings of the Eleventh International Symposium on Imprecise Probabilities : Theories and Applications. In Proceedings of Machine Learning Research 103. p.394-403
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First steps towards an imprecise Poisson process

Alexander Erreygers (UGent) and Jasper De Bock (UGent)

(2019) Proceedings of the Eleventh International Symposium on Imprecise Probabilities : Theories and Applications, ISIPTA 2019. In Proceedings of Machine Learning Research 103. p.175-184
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Monte Carlo estimation for imprecise probabilities : basic properties

Arne Decadt (UGent) , Gert De Cooman (UGent) and Jasper De Bock (UGent)

(2019) International Symposium on Imprecise Probabilities : Theories and Applications, ISIPTA 2019, Proceedings. In Proceedings of Machine Learning Research 103. p.135-144

Academic Bibliography

Extending the domain of imprecise jump processes from simple variables to measurable ones

In search of a global belief model for discrete-time uncertain processes

Hitting times and probabilities for imprecise Markov chains

Two-state imprecise Markov chains for statistical modelling of two-state non-Markovian processes

First steps towards an imprecise Poisson process

Monte Carlo estimation for imprecise probabilities : basic properties

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