Konstantin Sidorov, Gonçalo Homem de Almeida Correia, Mathijs de Weerdt, Emir Demirović (2024), Paths, Proofs, and Perfection: Developing a Human-Interpretable Proof System for Constrained Shortest Paths, In Proceedings of the AAAI Conference on Artificial Intelligence p.20794-20802.

Laurens Bliek, Arthur Guijt, Rickard Karlsson, Sicco Verwer, Mathijs de Weerdt (2023), Benchmarking surrogate-based optimisation algorithms on expensive black-box functions, In Applied Soft Computing Volume 147.

Issa K. Hanou, Mathijs M. de Weerdt, Jesse Mulderij (2023), Moving Trains like Pebbles: A Feasibility Study on Tree Yards, In Proceedings International Conference on Automated Planning and Scheduling, ICAPS p.482-490.

J.G.M. van der Linden, M.M. de Weerdt, E. Demirović (2023), Necessary and Sufficient Conditions for Optimal Decision Trees using Dynamic Programming, A. Oh, T. Neumann, A. Globerson, K. Saenko, M. Hardt, S. Levine (Eds.), In Advances in Neural Information Processing Systems 36 (NeurIPS 2023) Volume 36 p.9173-9212, Curran Associates, Inc..

I. D. Serna-Suárez, G. Morales-España, M. de Weerdt, G. Carrillo-Caicedo, G. Ordóñez-Plata, O. A. Quiroga (2023), On the applicability of single-line equivalents on optimal operation of modern unbalanced distribution networks, In Electric Power Systems Research Volume 223.

Kim Van Den Houten, Mathijs De Weerdt, David M.J. Tax, Esteban Freydell, Eva Christoupoulou, Alessandro Nati (2023), Rolling-Horizon Simulation Optimization For A Multi-Objective Biomanufacturing Scheduling Problem, In Proceedings of the 2023 Winter Simulation Conference (WSC) p.1912-1923, IEEE.

G. Veviurko, J.W. Böhmer, M.M. de Weerdt (2023), You Shall not Pass: the Zero-Gradient Problem in Predict and Optimize for Convex Optimization.

Junhan Wen, Thomas Abeel, Mathijs de Weerdt (2023), “How sweet are your strawberries?”: Predicting sugariness using non-destructive and affordable hardware, In Frontiers in Plant Science Volume 14.

G. Neustroev, Sytze P.E. Andringa, Remco A. Verzijlbergh, Mathijs M. de Weerdt (2022), Deep Reinforcement Learning for Active Wake Control, In International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022 p.944-953, International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).

J.G.M. van der Linden, M.M. de Weerdt, E. Demirović (2022), Fair and Optimal Decision Trees: A Dynamic Programming Approach, S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, A. Oh (Eds.), In Advances in Neural Information Processing Systems 35 (NeurIPS 2022) p.38899-38911, Curran Associates, Inc..