| An empirical study of assumptions in Bayesian optimisation AI Cowen-Rivers, W Lyu, R Tutunov, Z Wang, A Grosnit, RR Griffiths, ... arXiv preprint arXiv:2012.03826 445, 2020 | 78* | 2020 |
| Hebo: Pushing the limits of sample-efficient hyper-parameter optimisation AI Cowen-Rivers, W Lyu, R Tutunov, Z Wang, A Grosnit, RR Griffiths, ... Journal of Artificial Intelligence Research 74, 1269-1349, 2022 | 59 | 2022 |
| High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning A Grosnit, R Tutunov, AM Maraval, RR Griffiths, AI Cowen-Rivers, L Yang, ... arXiv preprint arXiv:2106.03609, 2021 | 54 | 2021 |
| Efficient Semi-Implicit Variational Inference V Moens, H Ren, A Maraval, R Tutunov, J Wang, H Ammar arXiv preprint arXiv:2101.06070, 2021 | 5 | 2021 |
| End-to-end meta-bayesian optimisation with transformer neural processes A Maraval, M Zimmer, A Grosnit, H Bou Ammar Advances in Neural Information Processing Systems 36, 2024 | 4 | 2024 |
| Indicators of Risk Appetite and Applications in Trading AM Maraval | 2* | |
| Sample-Efficient Optimisation with Probabilistic Transformer Surrogates A Maraval, M Zimmer, A Grosnit, R Tutunov, J Wang, HB Ammar arXiv preprint arXiv:2205.13902, 2022 | 1 | 2022 |
