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Leonard Hasenclever
Leonard Hasenclever
Research Scientist at DeepMind
Email confirmado em google.com - Página inicial
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Ano
Sylvester Normalizing Flows for Variational Inference
R Berg, L Hasenclever, JM Tomczak, M Welling
UAI, 2018
2412018
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
1472018
Meta reinforcement learning as task inference
J Humplik, A Galashov, L Hasenclever, PA Ortega, YW Teh, N Heess
arXiv preprint arXiv:1905.06424, 2019
1322019
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
1232023
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
1192020
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
1082022
Information asymmetry in KL-regularized RL
A Galashov, SM Jayakumar, L Hasenclever, D Tirumala, J Schwarz, ...
International Conference on Learning Representations, 2018
1012018
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
922018
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
80*2017
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
752020
Observational learning by reinforcement learning
D Borsa, B Piot, R Munos, O Pietquin
arXiv preprint arXiv:1706.06617, 2017
722017
The true cost of stochastic gradient Langevin dynamics
T Nagapetyan, AB Duncan, L Hasenclever, SJ Vollmer, L Szpruch, ...
arXiv preprint arXiv:1706.02692, 2017
612017
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
472024
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
462020
Relativistic Monte Carlo
X Lu, V Perrone, L Hasenclever, YW Teh, SJ Vollmer
AISTATS, 2017
462017
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
432019
Towards a unified agent with foundation models
N Di Palo, A Byravan, L Hasenclever, M Wulfmeier, N Heess, ...
arXiv preprint arXiv:2307.09668, 2023
352023
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
332022
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
332022
Divide-and-conquer monte carlo tree search for goal-directed planning
G Parascandolo, L Buesing, J Merel, L Hasenclever, J Aslanides, ...
arXiv preprint arXiv:2004.11410, 2020
312020
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