| Bayesian low-rank adaptation for large language models AX Yang, M Robeyns, X Wang, L Aitchison arXiv preprint arXiv:2308.13111, 2023 | 8 | 2023 |
| A theory of representation learning gives a deep generalisation of kernel methods AX Yang, M Robeyns, E Milsom, B Anson, N Schoots, L Aitchison International Conference on Machine Learning, 39380-39415, 2023 | 7 | 2023 |
| A theory of representation learning in deep neural networks gives a deep generalisation of kernel methods AX Yang, M Robeyns, E Milsom, N Schoots, L Aitchison arXiv e-prints, arXiv: 2108.13097, 2021 | 4 | 2021 |
| Bayesian Reward Models for LLM Alignment AX Yang, M Robeyns, T Coste, J Wang, H Bou-Ammar, L Aitchison arXiv preprint arXiv:2402.13210, 2024 | | 2024 |
| Taylor TD-learning M Garibbo, M Robeyns, L Aitchison Advances in Neural Information Processing Systems 36, 2024 | | 2024 |
| A theory of representation learning in neural networks gives a deep generalisation of kernel methods AX Yang, M Robeyns, E Milsom, N Schoots, L Aitchison | | 2022 |
| Fast Estimation of Physical Galaxy Properties using Simulation-Based Inference M Robeyns, M Walmsley, S Fotopoulou, L Aitchison Machine Learning for Astrophysics, 12, 2022 | | 2022 |
