Spiking Neural PID Controllers. - Andrew M. Webb 002; Sergio Davies; David R. Lester (ICONIP (3), 2011)

Studying the Evolvability of of Self-Encoding Genotype-Phenotype Maps. - Andrew M. Webb 002; Joshua D. Knowles (ALIFE, 2014)

How Much Should You Select for Evolvability? - Andrew M. Webb 002; Julia Handl; Joshua D. Knowles (ECAL, 2015)

On selection for evolvability. - Andrew M. Webb 002 (2017)

Navigating the Landscape for Real-time Localisation and Mapping for Robotics and Virtual and Augmented Reality. - Sajad Saeedi 001; Bruno Bodin; Harry Wagstaff; Andy Nisbet; Luigi Nardi; John Mawer; Nicolas Melot; Oscar Palomar; Emanuele Vespa; Tom Spink; Cosmin Gorgovan; Andrew M. Webb 002; et al. (CoRR, 2018)

Navigating the Landscape for Real-Time Localization and Mapping for Robotics and Virtual and Augmented Reality. - Sajad Saeedi 001; Bruno Bodin; Harry Wagstaff; Andy Nisbet; Luigi Nardi; John Mawer; Nicolas Melot; Oscar Palomar; Emanuele Vespa; Tom Spink; Cosmin Gorgovan; Andrew M. Webb 002; et al. (Proc. IEEE, 2018)

Evolving controllably difficult datasets for clustering. - Cameron Shand; Richard Allmendinger 001; Julia Handl; Andrew M. Webb 002; John Keane (GECCO, 2019)

ORB-SLAM-CNN: Lessons in Adding Semantic Map Construction to Feature-Based SLAM. - Andrew M. Webb 002; Gavin Brown 001; Mikel Luján (TAROS (1), 2019)

Joint Training of Neural Network Ensembles. - Andrew M. Webb 002; Charles Reynolds; Dan-Andrei Iliescu; Henry W. J. Reeve; Mikel Luján; Gavin Brown 001 (CoRR, 2019)

To Ensemble or Not Ensemble: When Does End-to-End Training Fail? - Andrew M. Webb 002; Charles Reynolds; Wenlin Chen; Henry W. J. Reeve; Dan-Andrei Iliescu; Mikel Luján; Gavin Brown 001 (ECML/PKDD (3), 2020)

HAWKS: Evolving Challenging Benchmark Sets for Cluster Analysis. - Cameron Shand; Richard Allmendinger 001; Julia Handl; Andrew M. Webb 002; John Keane (IEEE Trans. Evol. Comput., 2022)

A Unified Theory of Diversity in Ensemble Learning. - Danny Wood; Tingting Mu; Andrew M. Webb 002; Henry W. J. Reeve; Mikel Luján; Gavin Brown 001 (J. Mach. Learn. Res., 2023)