| Bayesian batch active learning as sparse subset approximation R Pinsler, J Gordon, E Nalisnick, JM Hernández-Lobato Advances in Neural Information Processing Systems, 6359-6370, 2019 | 70 | 2019 |
| Reinforcement Learning for Molecular Design Guided by Quantum Mechanics GNC Simm, R Pinsler, JM Hernández-Lobato International Conference on Machine Learning, 8959-8969, 2020 | 51 | 2020 |
| Symmetry-Aware Actor-Critic for 3D Molecular Design GNC Simm, R Pinsler, G Csányi, JM Hernández-Lobato International Conference on Learning Representations, 2021 | 26 | 2021 |
| Sample and feedback efficient hierarchical reinforcement learning from human preferences R Pinsler, R Akrour, T Osa, J Peters, G Neumann 2018 IEEE International Conference on Robotics and Automation (ICRA), 596-601, 2018 | 19 | 2018 |
| Inverse Reinforcement Learning of Bird Flocking Behavior R Pinsler, M Maag, O Arenz, G Neumann ICRA 2018 Workshop on Swarms: From Biology to Robotics and Back, 2018 | 7 | 2018 |
| Factored Contextual Policy Search with Bayesian Optimization R Pinsler, P Karkus, A Kupcsik, D Hsu, WS Lee 2019 IEEE International Conference on Robotics and Automation (ICRA), 7242-7248, 2019 | 4 | 2019 |
| 3D Molecular Design with Covariant Neural Networks GNC Simm, R Pinsler, G Csányi, JM Hernández-Lobato NeurIPS Workshop on Machine Learning for Molecules, 2020 | | 2020 |
José Miguel Hernández-LobatoAssociate Professor in Machine Learning, University of CambridgeVerified email at cam.ac.uk
