Evolving Instinctive Behaviour in Resource-Constrained Autonomous Agents Using Grammatical Evolution. - Ahmed Hallawa; Simon Schug; Giovanni Iacca; Gerd Ascheid (EvoApplications, 2020)

Learning where to learn: Gradient sparsity in meta and continual learning. - Johannes von Oswald; Dominic Zhao; Seijin Kobayashi; Simon Schug; Massimo Caccia; Nicolas Zucchet; João Sacramento (NeurIPS, 2021)

A contrastive rule for meta-learning. - Nicolas Zucchet; Simon Schug; Johannes von Oswald; Dominic Zhao; João Sacramento (NeurIPS, 2022)

Random initialisations performing above chance and how to find them. - Frederik Benzing; Simon Schug; Robert Meier; Johannes von Oswald; Yassir Akram; Nicolas Zucchet; Laurence Aitchison; Angelika Steger (CoRR, 2022)

Would I have gotten that reward? Long-term credit assignment by counterfactual contribution analysis. - Alexander Meulemans; Simon Schug; Seijin Kobayashi; Nathaniel Daw; Gregory Wayne (NeurIPS, 2023)

Online learning of long-range dependencies. - Nicolas Zucchet; Robert Meier; Simon Schug; Asier Mujika; João Sacramento (NeurIPS, 2023)

Discovering modular solutions that generalize compositionally. - Simon Schug; Seijin Kobayashi; Yassir Akram; Maciej Wolczyk; Alexandra Proca; Johannes von Oswald; Razvan Pascanu; João Sacramento; Angelika Steger (ICLR, 2024)

When can transformers compositionally generalize in-context? - Seijin Kobayashi; Simon Schug; Yassir Akram; Florian Redhardt; Johannes von Oswald; Razvan Pascanu; Guillaume Lajoie; João Sacramento (CoRR, 2024)

Attention as a Hypernetwork. - Simon Schug; Seijin Kobayashi; Yassir Akram; João Sacramento; Razvan Pascanu (ICLR, 2025)

Scale leads to compositional generalization. - Florian Redhardt; Yassir Akram; Simon Schug (CoRR, 2025)