Dirk van Bokkem, Max van den Hemel, Sebastijan Dumančić, Neil Yorke-Smith (2023), Embedding a Long Short-Term Memory Network in a Constraint Programming Framework for Tomato Greenhouse Optimisation, Brian Williams, Yiling Chen, Jennifer Neville (Eds.), In AAAI-23 Special Programs, IAAI-23, EAAI-23, Student Papers and Demonstrations p.15731-15737, American Association for Artificial Intelligence (AAAI).

A. Dushatskiy (2023), Expensive Optimization with Model-Based Evolutionary Algorithms Applied to Medical Image Segmentation Using Deep Learning, PhD Thesis Delft University of Technology.

Roland Saur, Han La Poutré, Neil Yorke-Smith (2023), Fair Pricing for Time-Flexible Smart Energy Markets, In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS p.2703-2705.

Isaak L. Geursen, Bruno F. Santos, N. Yorke-Smith (2023), Fleet planning under demand and fuel price uncertainty using actor–critic reinforcement learning, In Journal of Air Transport Management Volume 109.

Philippe de Bekker, Sho Cremers, Sonam Norbu, David Flynn, Valentin Robu (2023), Improving the efficiency of renewable energy assets by optimizing the matching of supply and demand using a smart battery scheduling algorithm, In Energies Volume 16.

Konstantin Kueffner, Anna Lukina, Christian Schilling, Thomas A. Henzinger (2023), Into the unknown: active monitoring of neural networks (extended version), In International Journal on Software Tools for Technology Transfer Volume 25 p.575-592.

Álvaro Serra-Gómez, Hai Zhu, B.F. Ferreira de Brito, Wendelin Böhmer, Javier Alonso-Mora (2023), Learning scalable and efficient communication policies for multi-robot collision avoidance, In Autonomous Robots Volume 47 p.1275-1297.

Pankaj R. Telang, Munindar P. Singh, Neil Yorke-Smith (2023), Maintenance commitments: Conception, semantics, and coherence, In Artificial Intelligence Volume 324.

Joe Harrison, Marco Virgolin, Tanja Alderliesten, Peter Bosman (2023), Mini-Batching, Gradient-Clipping, First-versus Second-Order: What Works in Gradient-Based Coefficient Optimisation for Symbolic Regression', In GECCO 2023 - Proceedings of the 2023 Genetic and Evolutionary Computation Conference p.1127-1136, Association for Computing Machinery (ACM).

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.