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0000-0002-5540-7858
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- PhD Thesis
- open access
Upper expectations for discrete-time imprecise stochastic processes : in practice, they are all the same!
(2022) -
- Conference Paper
- P1
- open access
Average behaviour of imprecise Markov chains : a single pointwise ergodic theorem for six different models
(2021) PROCEEDINGS OF MACHINE LEARNING RESEARCH. In Proceedings of Machine Learning Research 147. p.90-99 -
- Conference Paper
- P1
- open access
Global upper expectations for discrete-time stochastic processes : in practice, they are all the same!
(2021) PROCEEDINGS OF MACHINE LEARNING RESEARCH. In Proceedings of Machine Learning Research 147. p.310-319 -
- Journal Article
- A1
- open access
Game-theoretic upper expectations for discrete-time finite-state uncertain processes
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Average behaviour in discrete-time imprecise Markov chains : a study of weak ergodicity
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A particular upper expectation as global belief model for discrete-time finite-state uncertain processes
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- Conference Paper
- C1
- open access
Limit behaviour of upper and lower expected time averages in discrete-time imprecise Markov chains
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A recursive algorithm for computing inferences in imprecise Markov chains
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- Conference Paper
- C1
- open access
Hitting times and probabilities for imprecise Markov chains
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- Conference Paper
- C1
- open access
In search of a global belief model for discrete-time uncertain processes