Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A.N. Bosman (2024), Exploring the Search Space of Neural Network Combinations obtained with Efficient Model Stitching, In GECCO '24 Companion p.1914-1923, Association for Computing Machinery (ACM).

Giuseppe Marra, Sebastijan Dumančić, Robin Manhaeve, Luc De Raedt (2024), From statistical relational to neurosymbolic artificial intelligence: A survey, In Artificial Intelligence.

Heye Huang, Yicong Liu, Jinxin Liu, Qisong Yang, Jianqiang Wang, David Abbink, Arkady Zgonnikov (2024), General Optimal Trajectory Planning: Enabling Autonomous Vehicles with the Principle of Least Action, In Engineering Volume 33 p.63-76.

Alexander Chebykin, Peter A.N. Bosman, Tanja Alderliesten (2024), Hyperparameter-free medical image synthesis for sharing data and improving site-specific segmentation.

Germán Morales-España, Ricardo Hernández-Serna, Diego A. Tejada-Arango, Marcel Weeda (2024), Impact of large-scale hydrogen electrification and retrofitting of natural gas infrastructure on the European power system, In International Journal of Electrical Power and Energy Systems Volume 155.

N.J. Schutte, N. Yorke-Smith, K.S. Postek (2024), Improving Metaheuristic Efficiency for Stochastic Optimization by Sequential Predictive Sampling, In Lecture Notes in Computer Science Volume 14743 p.158-175.

R. Saur, J.A. la Poutré, N. Yorke-Smith (2024), Incentives for Accurate Energy Predictions: How to Reduce Epistemic Uncertainty, In Proceedings of the e-Energy '24 p.192 - 202.

Leah R.M. Dickhoff, Renzo J. Scholman, Danique L.J. Barten, Ellen M. Kerkhof, Jelmen J. Roorda, Laura A. Velema, Lukas J.A. Stalpers, Bradley R. Pieters, Peter A.N. Bosman, Tanja Alderliesten (2024), Keeping your best options open with AI-based treatment planning in prostate and cervix brachytherapy, In Brachytherapy p.188-198.

Kim van den Houten, David M.J. Tax, Esteban Freydell, Mathijs de Weerdt (2024), Learning from Scenarios for Repairable Stochastic Scheduling, Bistra Dilkina (Eds.), In Integration of Constraint Programming, Artificial Intelligence, and Operations Research - 21st International Conference, CPAIOR 2024, Proceedings p.234-242, Springer.

Yun Li, Neil Yorke-Smith, Tamas Keviczky (2024), Machine learning enabled uncertainty set for data-driven robust optimization, In Journal of Process Control Volume 144.