| Safe policy search for lifelong reinforcement learning with sublinear regret HB Ammar, R Tutunov, E Eaton International Conference on Machine Learning, 2361-2369, 2015 | 82 | 2015 |
| 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 | 81 | 2022 |
| Distributed newton method for large-scale consensus optimization R Tutunov, H Bou-Ammar, A Jadbabaie IEEE Transactions on Automatic Control 64 (10), 3983-3994, 2019 | 74 | 2019 |
| 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 | 61 | 2021 |
| 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 | 49 | 2020 |
| Hebo: Heteroscedastic evolutionary bayesian optimisation AI Cowen-Rivers, W Lyu, Z Wang, R Tutunov, H Jianye, J Wang, ... arXiv preprint arXiv:2012.03826 7, 2020 | 38 | 2020 |
| Toward real-world automated antibody design with combinatorial Bayesian optimization A Khan, AI Cowen-Rivers, A Grosnit, PA Robert, V Greiff, E Smorodina, ... Cell Reports Methods 3 (1), 2023 | 37 | 2023 |
| Boils: Bayesian optimisation for logic synthesis A Grosnit, C Malherbe, R Tutunov, X Wan, J Wang, HB Ammar 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2022 | 35 | 2022 |
| -Rank: Practically Scaling -Rank through Stochastic Optimisation Y Yang, R Tutunov, P Sakulwongtana, HB Ammar arXiv preprint arXiv:1909.11628, 2019 | 27 | 2019 |
| Compositional adam: An adaptive compositional solver R Tutunov, M Li, AI Cowen-Rivers, J Wang, H Bou-Ammar arXiv preprint arXiv:2002.03755, 2020 | 20 | 2020 |
| Antbo: Towards real-world automated antibody design with combinatorial bayesian optimisation A Khan, AI Cowen-Rivers, A Grosnit, DGX Deik, PA Robert, V Greiff, ... arXiv preprint arXiv:2201.12570, 2022 | 19 | 2022 |
| Are we forgetting about compositional optimisers in Bayesian optimisation? A Grosnit, AI Cowen-Rivers, R Tutunov, RR Griffiths, J Wang, ... Journal of Machine Learning Research 22 (160), 1-78, 2021 | 17 | 2021 |
| Graph attention memory for visual navigation D Li, Q Zhang, D Zhao 2022 4th International Conference on Data-driven Optimization of Complex …, 2022 | 13 | 2022 |
| Distributed multitask reinforcement learning with quadratic convergence R Tutunov, D Kim, H Bou Ammar Advances in neural information processing systems 31, 2018 | 13 | 2018 |
| Why Can Large Language Models Generate Correct Chain-of-Thoughts? R Tutunov, A Grosnit, J Ziomek, J Wang, H Bou-Ammar arXiv preprint arXiv:2310.13571, 2023 | 12 | 2023 |
| HEBO pushing the limits of sample-efficient hyperparameter optimisation AI Cowen-Rivers, W Lyu, R Tutunov, Z Wang, A Grosnit, RR Griffiths, ... arXiv preprint arXiv:2012.03826, 2020 | 12 | 2020 |
| BOiLS: Bayesian optimisation for logic synthesis. In 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE) A Grosnit, C Malherbe, R Tutunov, X Wan, J Wang, HB Ammar IEEE, 2022 | 9 | 2022 |
| Efficient semi-implicit variational inference V Moens, H Ren, A Maraval, R Tutunov, J Wang, H Ammar arXiv preprint arXiv:2101.06070, 2021 | 9 | 2021 |
| Distributed SDDM solvers: Theory & applications R Tutunov, H Bou-Ammar, A Jadbabaie arXiv preprint arXiv:1508.04096, 2015 | 9 | 2015 |
| Derivative-free & order-robust optimisation H Ammar, V Gabillon, R Tutunov, M Valko International Conference on Artificial Intelligence and Statistics, 2293-2303, 2020 | 8 | 2020 |
