Hasenclever, Leonard

From motor control to team play in simulated humanoid football

Liu, S., Lever, G., Wang, Z., Merel, J., Eslami, S. M. A., Hennes, D., Czarnecki, W. M., Tassa, Y., Omidshafiei, S., Abdolmaleki, A., et al. (2022) · Science Robotics

Reinforcement Learning in RoboticsHuman Motion and Animation

Cited by 88

Meta reinforcement learning as task inference

Humplik, J., Galashov, A., Hasenclever, L., Ortega, P. A., Teh, Y. W., & Heess, N. (2019) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 82

A virtual rodent predicts the structure of neural activity across behaviours

Aldarondo, D., Merel, J., Marshall, J. D., Hasenclever, L., Klibaite, U., Gellis, A., Tassa, Y., Wayne, G., Botvinick, M., & Ölveczky, B. P. (2024) · Nature

Motor Control and AdaptationNeural dynamics and brain function

Cited by 70

Observational Learning by Reinforcement Learning

Borsa, D., Heess, N., Piot, B., Liu, S., Hasenclever, L., Munos, R., & Pietquin, O. (2019) · International Joint Conference on Autonomous Agents and Multiagent Systems

Reinforcement Learning in RoboticsChild and Animal Learning Development

Cited by 47

Towards A Unified Agent with Foundation Models

Di Palo, N., Byravan, A., Hasenclever, L., Wulfmeier, M., Heess, N., & Riedmiller, M. (2023) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 16

Gemini Robotics: Bringing AI into the Physical World

Gemini Robotics Team, Abeyruwan, S., Ainslie, J., Alayrac, J.-B., Arenas, M. G., Armstrong, T., Balakrishna, A., Baruch, R., Bauza, M., Blokzijl, M., et al. (2025) · arXiv

Robot Manipulation and LearningMultimodal Machine Learning Applications

Cited by 8