Jasper De Bock

Orcid: 0000-0003-1950-0059

According to our database1, Jasper De Bock authored at least 65 papers between 2012 and 2023.

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

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Bibliography

2023
The Twelfth International Symposium on Imprecise Probabilities: Theories and Applications (ISIPTA-21).
Int. J. Approx. Reason., 2023

The logic behind desirable sets of things, and its filter representation.
CoRR, 2023

Indistinguishability through exchangeability in quantum mechanics?
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 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

Desirable sets of things and their logic.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2023

A theory of desirable things.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2023

2022
On the (dis)similarities between stationary imprecise and non-stationary precise uncertainty models in algorithmic randomness.
Int. J. Approx. Reason., 2022

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

Randomness is inherently imprecise.
Int. J. Approx. Reason., 2022

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

2021
A particular upper expectation as global belief model for discrete-time finite-state uncertain processes.
Int. J. Approx. Reason., 2021

Average behaviour in discrete-time imprecise Markov chains: A study of weak ergodicity.
Int. J. Approx. Reason., 2021

On a notion of independence proposed by Teddy Seidenfeld.
CoRR, 2021

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

Global Upper Expectations for Discrete-Time Stochastic Processes: In Practice, They Are All The Same!
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2021

A Remarkable Equivalence between Non-Stationary Precise and Stationary Imprecise Uncertainty Models in Computable Randomness.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 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

Randomness and Imprecision: A Discussion of Recent Results.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2021

Average Behaviour of Imprecise Markov Chains: A Single Pointwise Ergodic Theorem for Six Different Models.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2021

The Smallest Probability Interval a Sequence Is Random for: A Study for Six Types of Randomness.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2021

2020
A Robust Dynamic Classifier Selection Approach for Hyperspectral Images with Imprecise Label Information.
Sensors, 2020

Choice functions based on sets of strict partial orders: an axiomatic characterisation.
CoRR, 2020

Computable Randomness Is About More Than Probabilities.
Proceedings of the Scalable Uncertainty Management - 14th International Conference, 2020

Inference with Choice Functions Made Practical.
Proceedings of the Scalable Uncertainty Management - 14th International Conference, 2020

Limit Behaviour of Upper and Lower Expected Time Averages in Discrete-Time Imprecise Markov Chains.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2020

Archimedean Choice Functions - An Axiomatic Foundation for Imprecise Decision Making.
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

Independent natural extension for infinite spaces.
Int. J. Approx. Reason., 2019

An alternative approach to coherent choice functions.
CoRR, 2019

In Search of a Global Belief Model for Discrete-Time Uncertain Processes.
Proceedings of the International Symposium on Imprecise Probabilities: Theories and Applications, 2019

Hitting Times and Probabilities for Imprecise Markov Chains.
Proceedings of the International Symposium on Imprecise Probabilities: Theories and Applications, 2019

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

Monte Carlo Estimation for Imprecise Probabilities: Basic Properties.
Proceedings of the International Symposium on Imprecise Probabilities: Theories and Applications, 2019

Interpreting, Axiomatising and Representing Coherent Choice Functions in Terms of Desirability.
Proceedings of the International Symposium on Imprecise Probabilities: Theories and Applications, 2019

A Recursive Algorithm for Computing Inferences in Imprecise Markov Chains.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2019

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

Continuity of the Shafer-Vovk-Ville Operator.
Proceedings of the Uncertainty Modelling in Data Science, 2018

Dynamic Classifier Selection Based on Imprecise Probabilities: A Case Study for the Naive Bayes Classifier.
Proceedings of the Uncertainty Modelling in Data Science, 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

A Desirability-Based Axiomatisation for Coherent Choice Functions.
Proceedings of the Uncertainty Modelling in Data Science, 2018

2017
The Limit Behaviour of Imprecise Continuous-Time Markov Chains.
J. Nonlinear Sci., 2017

Computing lower and upper expected first-passage and return times in imprecise birth-death chains.
Int. J. Approx. Reason., 2017

Imprecise continuous-time Markov chains.
Int. J. Approx. Reason., 2017

Credal networks under epistemic irrelevance.
Int. J. Approx. Reason., 2017

Efficient Computation of Updated Lower Expectations for Imprecise Continuous-Time Hidden Markov Chains.
Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications, 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

Computable Randomness is Inherently Imprecise.
Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications, 2017

Independent Natural Extension for Infinite Spaces: Williams-Coherence to the Rescue.
Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications, 2017

Coherent Predictive Inference under Exchangeability with Imprecise Probabilities (Extended Abstract).
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016
Robust queueing theory: an initial study using imprecise probabilities.
Queueing Syst. Theory Appl., 2016

Imprecise stochastic processes in discrete time: global models, imprecise Markov chains, and ergodic theorems.
Int. J. Approx. Reason., 2016

Representation theorems for partially exchangeable random variables.
Fuzzy Sets Syst., 2016

Reintroducing Credal Networks under Epistemic Irrelevance.
Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

Exploiting Bayesian Network Sensitivity Functions for Inference in Credal Networks.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

2015
Coherent Predictive Inference under Exchangeability with Imprecise Probabilities.
J. Artif. Intell. Res., 2015

Conditioning, updating and lower probability zero.
Int. J. Approx. Reason., 2015

Credal networks under epistemic irrelevance: The sets of desirable gambles approach.
Int. J. Approx. Reason., 2015

2014
An Efficient Algorithm for Estimating State Sequences in Imprecise Hidden Markov Models.
J. Artif. Intell. Res., 2014

Robustifying the Viterbi Algorithm.
Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

Global Sensitivity Analysis for MAP Inference in Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Extreme Lower Previsions and Minkowski Indecomposability.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2013

2012
Credal nets under epistemic irrelevance
CoRR, 2012

Imprecise Bernoulli Processes.
Proceedings of the Advances in Computational Intelligence, 2012

Recent advances in imprecise-probabilistic graphical models.
Proceedings of the ECAI 2012, 2012


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