Alexander Erreygers

Orcid: 0000-0002-0409-2999

According to our database1, Alexander Erreygers authored at least 13 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Expected time averages in Markovian imprecise jump processes: a graph-theoretic characterisation of weak ergodicity.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2023

Sublinear expectations for countable-state uncertain processes.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2023

2022
Markovian imprecise jump processes: Extension to measurable variables, convergence theorems and algorithms.
Int. J. Approx. Reason., 2022

Decision-making with E-admissibility given a finite assessment of choices.
CoRR, 2022

2021
Sum-product laws and efficient algorithms for imprecise Markov chains.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Extending the Domain of Imprecise Jump Processes from Simple Variables to Measurable Ones.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2021

2020
A Study of the Set of Probability Measures Compatible with Comparative Judgements.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2020

2019
Bounding inferences for large-scale continuous-time Markov chains: A new approach based on lumping and imprecise Markov chains.
Int. J. Approx. Reason., 2019

First Steps Towards an Imprecise Poisson Process.
Proceedings of the International Symposium on Imprecise Probabilities: Theories and Applications, 2019

2018
Imprecise Markov Models for Scalable and Robust Performance Evaluation of Flexi-Grid Spectrum Allocation Policies.
IEEE Trans. Commun., 2018

An Imprecise Probabilistic Estimator for the Transition Rate Matrix of a Continuous-Time Markov Chain.
Proceedings of the Uncertainty Modelling in Data Science, 2018

Computing Inferences for Large-Scale Continuous-Time Markov Chains by Combining Lumping with Imprecision.
Proceedings of the Uncertainty Modelling in Data Science, 2018

2017
Imprecise Continuous-Time Markov Chains: Efficient Computational Methods with Guaranteed Error Bounds.
Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications, 2017


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