| Sylvester Normalizing Flows for Variational Inference R Berg, L Hasenclever, JM Tomczak, M Welling UAI, 2018 | 253 | 2018 |
| Language to rewards for robotic skill synthesis W Yu, N Gileadi, C Fu, S Kirmani, KH Lee, MG Arenas, HTL Chiang, ... arXiv preprint arXiv:2306.08647, 2023 | 192 | 2023 |
| Neural probabilistic motor primitives for humanoid control J Merel, L Hasenclever, A Galashov, A Ahuja, V Pham, G Wayne, YW Teh, ... arXiv preprint arXiv:1811.11711, 2018 | 159 | 2018 |
| Meta reinforcement learning as task inference J Humplik, A Galashov, L Hasenclever, PA Ortega, YW Teh, N Heess arXiv preprint arXiv:1905.06424, 2019 | 141 | 2019 |
| Catch & carry: reusable neural controllers for vision-guided whole-body tasks J Merel, S Tunyasuvunakool, A Ahuja, Y Tassa, L Hasenclever, V Pham, ... ACM Transactions on Graphics (TOG) 39 (4), 39: 1-39: 12, 2020 | 129 | 2020 |
| From motor control to team play in simulated humanoid football S Liu, G Lever, Z Wang, J Merel, SMA Eslami, D Hennes, WM Czarnecki, ... Science Robotics 7 (69), eabo0235, 2022 | 118 | 2022 |
| Information asymmetry in KL-regularized RL A Galashov, SM Jayakumar, L Hasenclever, D Tirumala, J Schwarz, ... International Conference on Learning Representations, 2018 | 106 | 2018 |
| Mix & match agent curricula for reinforcement learning W Czarnecki, S Jayakumar, M Jaderberg, L Hasenclever, YW Teh, ... International Conference on Machine Learning, 1087-1095, 2018 | 90 | 2018 |
| Learning agile soccer skills for a bipedal robot with deep reinforcement learning T Haarnoja, B Moran, G Lever, SH Huang, D Tirumala, J Humplik, ... Science Robotics 9 (89), eadi8022, 2024 | 87 | 2024 |
| A distributional view on multi-objective policy optimization A Abdolmaleki, S Huang, L Hasenclever, M Neunert, F Song, M Zambelli, ... International conference on machine learning, 11-22, 2020 | 84 | 2020 |
| Distributed Bayesian learning with stochastic natural gradient expectation propagation and the posterior server L Hasenclever, S Webb, T Lienart, S Vollmer, B Lakshminarayanan, ... Journal of Machine Learning Research 18 (106), 1-37, 2017 | 81* | 2017 |
| Observational learning by reinforcement learning D Borsa, B Piot, R Munos, O Pietquin arXiv preprint arXiv:1706.06617, 2017 | 75 | 2017 |
| The true cost of stochastic gradient Langevin dynamics T Nagapetyan, AB Duncan, L Hasenclever, SJ Vollmer, L Szpruch, ... arXiv preprint arXiv:1706.02692, 2017 | 62 | 2017 |
| CoMic: Complementary task learning & mimicry for reusable skills L Hasenclever, F Pardo, R Hadsell, N Heess, J Merel International Conference on Machine Learning, 4105-4115, 2020 | 51 | 2020 |
| Relativistic Monte Carlo X Lu, V Perrone, L Hasenclever, YW Teh, SJ Vollmer AISTATS, 2017 | 48 | 2017 |
| Towards a unified agent with foundation models N Di Palo, A Byravan, L Hasenclever, M Wulfmeier, N Heess, ... arXiv preprint arXiv:2307.09668, 2023 | 46 | 2023 |
| Exploiting hierarchy for learning and transfer in kl-regularized rl D Tirumala, H Noh, A Galashov, L Hasenclever, A Ahuja, G Wayne, ... arXiv preprint arXiv:1903.07438, 2019 | 44 | 2019 |
| Imitate and repurpose: Learning reusable robot movement skills from human and animal behaviors S Bohez, S Tunyasuvunakool, P Brakel, F Sadeghi, L Hasenclever, ... arXiv preprint arXiv:2203.17138, 2022 | 41 | 2022 |
| Behavior priors for efficient reinforcement learning D Tirumala, A Galashov, H Noh, L Hasenclever, R Pascanu, J Schwarz, ... Journal of Machine Learning Research 23 (221), 1-68, 2022 | 36 | 2022 |
| Nerf2real: Sim2real transfer of vision-guided bipedal motion skills using neural radiance fields A Byravan, J Humplik, L Hasenclever, A Brussee, F Nori, T Haarnoja, ... 2023 IEEE International Conference on Robotics and Automation (ICRA), 9362-9369, 2023 | 35 | 2023 |
