| Smarts: An open-source scalable multi-agent rl training school for autonomous driving M Zhou, J Luo, J Villella, Y Yang, D Rusu, J Miao, W Zhang, M Alban, ... Conference on robot learning, 264-285, 2021 | 205 | 2021 |
| 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 | 154* | 2022 |
| Sauté rl: Almost surely safe reinforcement learning using state augmentation A Sootla, AI Cowen-Rivers, T Jafferjee, Z Wang, DH Mguni, J Wang, ... International Conference on Machine Learning, 20423-20443, 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 | 58 | 2021 |
| Samba: Safe model-based & active reinforcement learning AI Cowen-Rivers, D Palenicek, V Moens, MA Abdullah, A Sootla, J Wang, ... Machine Learning 111 (1), 173-203, 2022 | 44 | 2022 |
| 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 | 31 | 2023 |
| Compositional Adam: An adaptive compositional solver AI Cowen-Rivers, R Tutunov, M Li, 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, ... Cell Reports Methods, 2022 | 17 | 2022 |
| Are we Forgetting about Compositional Optimisers in Bayesian Optimisation? HBA Alexander I. Cowen-Rivers, Antoine Grosnit, Rasul Tutunov, Ryan-Rhys ... JMLR, 2021 | 17* | 2021 |
| Enhancing safe exploration using safety state augmentation A Sootla, A Cowen-Rivers, J Wang, H Bou Ammar Advances in Neural Information Processing Systems 35, 34464-34477, 2022 | 15 | 2022 |
| 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 |
| Neural Variational Inference For Estimating Uncertainty in Knowledge Graph Embeddings AI Cowen-Rivers, P Minervini, T Rocktaschel, M Bosnjak, S Riedel, ... IJCAI Workshop on Neural- Symbolic Learning and Reasoning, 2019 | 6 | 2019 |
| Emergent Communication with World Models JN Alexander I. Cowen-Rivers NeurIPS Workshop on Emergent Communication, 2019 | 4* | 2019 |
| Towards incremental cylindrical algebraic decomposition in Maple ME Alexander Imani Cowen-Rivers FLoC 2018, 2018 | 4* | 2018 |
| Structured Q-learning For Antibody Design AI Cowen-Rivers, PJ Gorinski, A Sootla, A Khan, L Furui, J Wang, J Peters, ... arXiv preprint arXiv:2209.04698, 2022 | 2 | 2022 |
| Know Your Enemies and Know Yourself in the Real-Time Bidding Function Optimisation M Du, AI Cowen-Rivers, Y Wen, P Sakulwongtana, J Wang, M Brorsson, ... 2019 International Conference on Data Mining Workshops (ICDMW), 973-981, 2019 | 2* | 2019 |
| Learning geometric constraints in task and motion planning T Ren, AI Cowen-Rivers, HB Ammar, J Peters arXiv preprint arXiv:2201.09612, 2022 | 1 | 2022 |
| Pushing The Limits of Sample-Efficient Optimisation A Cowen-Rivers Technische Universität Darmstadt, 2023 | | 2023 |
| Effects of safety state augmentation on safe exploration A Sootla, AI Cowen-Rivers, J Wang, HB Ammar arXiv preprint arXiv:2206.02675, 2022 | | 2022 |
| RL: Generic reinforcement learning codebase in TensorFlow BM Li, A Cowen-Rivers, P Kozakowski, D Tao, SR Kamalakara, ... Journal of Open Source Software 4 (42), 1524, 2019 | | 2019 |
Haitham Bou-AmmarRL-Team Leader, BO-Team Leader, MAS-Team Leader @ Huawei London & H. Assistant Professor @ UCLGeverifieerd e-mailadres voor huawei.com
