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P.R. van der Vaart, N. Yorke-Smith, M.T.J. Spaan (2024), Bayesian Ensembles for Exploration in Deep Q-Learning, Natasha Alechina, Virginia Dignum (Eds.), In Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems p.2528-2530, International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).

Joery A de Vries, Jinke He, Mathijs de Weerdt, Matthijs TJ Spaan (2024), Bayesian Meta-Reinforcement Learning with Laplace Variational Recurrent Networks.

Ligia Maria Moreira Zorello, Laurens Bliek, Sebastian Troia, Guido Maier, Sicco Verwer (2024), Black-box optimization for anticipated baseband-function placement in 5G networks, In Computer Networks Volume 245.

C.S. Cao, Simon Schneider, Nicolás E. Díaz Ferreyra, S.E. Verwer, A. Panichella, Riccardo Scandariato (2024), CATMA: Conformance Analysis Tool For Microservice Applications, Ana Paiva, Abhik Roychoudhury, Margaret Storey (Eds.), In ACM/IEEE 46th International Conference on Software Engineering - Demonstrations p.59-63.

Azqa Nadeem (2024), Cybersecurity as a Crosscutting Concept Across an Undergrad Computer Science Curriculum: An Experience Report, In SIGCSE 2024 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education p.916-922, Association for Computing Machinery (ACM).

Kshitij Goyal, Sebastijan Dumancic, Hendrik Blockeel (2024), DeepSaDe: Learning Neural Networks That Guarantee Domain Constraint Satisfaction, Michael Wooldridge, Jennifer Dy, Sriraam Natarajan (Eds.), In Technical Tracks 14 Volume 38 p.12199-12207.

S. Hugtenburg, N. Yorke-Smith (2024), Delftse Foundations of Computation, TU Delft OPEN Publishing.

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Elif Arslan, Emir Demirović, Marco Rinaldi, Oded Cats, Serge Hoogendoorn (2024), Explainable Demand Prediction for Ride-Hailing Services.