Applying imprecise probabilities to stochastic processes

Continuous-Time Imprecise-Markov Chains: Theory and Algorithms

Decision-theoretic foundations of quantum mechanics

Doctoral project Arne Decadt

Doctoral project Jasper De Bock

Doctoral project Rolando Augusto Quiñones Lara

Doctoral project Stavros Lopatatzidis

Upper Expectations for Discrete-Time Imprecise Stochastic Processes: In Practice, They Are All the Same!

Decision making under uncertainty with imprecise probabilities

Algorithms for reasoning in credal trees

Bioinformatics: from nucleotids to networks (N2N)

Decision-theoretic foundations for classical and quantum probability

Developing the next generation of robust Bayesian networks: theory and efficient inference algorithms for mixed credal networks

Imprecise continuous-time Markov chains

Reasoning using desirability-based credal networks under epistemic irrelevance

Robust modelling and optimisation in stochastic processes using imprecise probabilities, with applications to queueing

Towards a more robust treatment of discrete-time stochastic processes: developing a theoretical framework for working with imprecise probabilities in Markov chains

Uncertainty Treatment and OPtimisation In Aerospace Engineering

Uncertainty Treatment and OPtimisation In Aerospace Engineering (UTOPIAE)

Efficient inference in large-scale queueing models using imprecise continuous-time Markov chains

IAP VII / 83 / Aeyels

Imprecise random sequences and their statistical estimation

Imprecise random sequences and their statistical estimation.