| Learning where to learn: Gradient sparsity in meta and continual learning J Von Oswald, D Zhao, S Kobayashi, S Schug, M Caccia, N Zucchet, ... Advances in Neural Information Processing Systems 34, 5250-5263, 2021 | 60 | 2021 |
| Random initialisations performing above chance and how to find them F Benzing, S Schug, R Meier, J von Oswald, Y Akram, N Zucchet, ... arXiv preprint arXiv:2209.07509, 2022 | 25 | 2022 |
| A contrastive rule for meta-learning N Zucchet*, S Schug*, J Von Oswald*, D Zhao, J Sacramento Advances in Neural Information Processing Systems 35, 25921-25936, 2022 | 24 | 2022 |
| Online learning of long-range dependencies N Zucchet*, R Meier*, S Schug*, A Mujika, J Sacramento Advances in Neural Information Processing Systems 36, 2024 | 19 | 2024 |
| Presynaptic stochasticity improves energy efficiency and helps alleviate the stability-plasticity dilemma S Schug*, F Benzing*, A Steger Elife 10, e69884, 2021 | 19 | 2021 |
| Evolving instinctive behaviour in resource-constrained autonomous agents using grammatical evolution A Hallawa, S Schug, G Iacca, G Ascheid Applications of Evolutionary Computation: 23rd European Conference …, 2020 | 13 | 2020 |
| Discovering modular solutions that generalize compositionally S Schug*, S Kobayashi*, Y Akram, M Wołczyk, A Proca, J von Oswald, ... The Twelfth International Conference on Learning Representations, 2024 | 12 | 2024 |
| Attention as a Hypernetwork S Schug, S Kobayashi, Y Akram, J Sacramento, R Pascanu arXiv preprint arXiv:2406.05816, 2024 | 5 | 2024 |
| Would I have gotten that reward? Long-term credit assignment by counterfactual contribution analysis A Meulemans*, S Schug*, S Kobayashi*, N Daw, G Wayne Advances in Neural Information Processing Systems 36, 2024 | 4 | 2024 |
| When can transformers compositionally generalize in-context? S Kobayashi*, S Schug*, Y Akram*, F Redhardt, J von Oswald, R Pascanu, ... arXiv preprint arXiv:2407.12275, 2024 | 1 | 2024 |
| A complementary systems theory of meta-learning S Schug, N Zucchet, J von Oswald, J Sacramento Computational and Systems Neuroscience (COSYNE 2023), 2023 | | 2023 |
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