Vitaly Kurin, Maximilian Igl, Tim Rocktäschel, Wendelin Böhmer, Shimon Whiteson (2021), My body is a cage: the role of morphology in graph-based incompatible control, In International Conference on Learning Representations (ICLR).

F.P. Doolaard, N. Yorke-Smith (2021), Online Learning of Deeper Variable Ordering Heuristics for Constraint Optimisation Problems, Edit Luis A. Leiva, Cédric Pruski, Réka Markovich, Amro Najjar, Christoph Schommer (Eds.), In BNAIC/BeneLearn 2021 p.789-791.

T. Þorbjarnarson, N. Yorke-Smith (2021), On Training Neural Networks with Mixed Integer Programming.

Menno Oudshoorn, Timo Koppenberg, Neil Yorke-Smith (2021), Optimization of annual planned rail maintenance, In Computer-Aided Civil and Infrastructure Engineering Volume 37 (2022) p.669-687.

Nicolas Schwind, Katsumi Inoue, E. Demirović (2021), Partial Robustness in Team Formation: Bridging the Gap between Robustness and Resilience, In Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems p.1154-1162.

Jordi Smit, Canmanie Ponnambalam, Matthijs T.J. Spaan, Frans A. Oliehoek (2021), PEBL: Pessimistic Ensembles for Offline Deep Reinforcement Learning, In Robust and Reliable Autonomy in the Wild Workshop at the 30th International Joint Conference of Artificial Intelligence.

Maizura Mokhtar, Valentin Robu, David Flynn, Ciaran Higgins, Jim Whyte, Caroline Loughran, Fiona Fulton (2021), Prediction of voltage distribution using deep learning and identified key smart meter locations, In Energy and AI Volume 6 p.1-10.

Nils H. van der Blij, Pavel Purgat, Thiago B. Soeiro, Laura M. Ramirez Elizondo, Matthijs T.J. Spaan, Pavol Bauer (2021), Protection Framework for Low Voltage DC Grids, In Proceedings - 2021 IEEE 19th International Power Electronics and Motion Control Conference, PEMC 2021 p.331-337.

Shariq Iqbal, Christian A. Schroeder de Witt, Bei Peng, Wendelin Böhmer, Shimon Whiteson, Fei Sha (2021), Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning, Marina Meila, Tong Zhang (Eds.), In Proceedings of the 37th International Conference on Machine Learning, ICML 2020 Volume 139 p.4596-4606.

Jacopo Pierotti, Maximilian Kronmueller, Javier Alonso-Mora, J. Theresia van Essen, Wendelin Böhmer (2021), Reinforcement Learning for the Knapsack Problem, In AIRO Springer Series p.3-13, Springer Nature.