Leonard Hasenclever

55 papers A* 7A 4Misc 2Journal 37Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Motion Tracking with Muscles: Predictive Control of a Parametric Musculoskeletal Canine Model. CoRR Vittorio La Barbera, Steven Bohez, Leonard Hasenclever, Yuval Tassa, John R. Hutchinson
2025	J	`jnl`	Proc4Gem: Foundation models for physical agency through procedural generation. CoRR Yixin Lin, Jan Humplik, Sandy H. Huang, Leonard Hasenclever, Francesco Romano, Stefano Saliceti, Daniel Zheng, José Enrique Chen, Catarina Barros, Adrian Collister, Matt Young, Adil Dostmohamed, Ben Moran, Ken Caluwaerts, Marissa Giustina, Joss Moore, Kieran Connell, Francesco Nori, Nicolas Heess, Steven Bohez, Arunkumar Byravan
2025	J	`jnl`	Splatting Physical Scenes: End-to-End Real-to-Sim from Imperfect Robot Data. CoRR Ben Moran, Mauro Comi, Arunkumar Byravan, Steven Bohez, Tom Erez, Zhibin Li, Leonard Hasenclever
2024	—	`conf`	Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning. CoLLAs Norman Di Palo, Leonard Hasenclever, Jan Humplik, Arunkumar Byravan
2024	J	`jnl`	Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning. CoRR Norman Di Palo, Leonard Hasenclever, Jan Humplik, Arunkumar Byravan
2024	Misc	`conf`	Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning. CoRL Dhruva Tirumala, Markus Wulfmeier, Ben Moran, Sandy H. Huang, Jan Humplik, Guy Lever, Tuomas Haarnoja, Leonard Hasenclever, Arunkumar Byravan, Nathan Batchelor, Neil Sreendra, Kushal Patel, Marlon Gwira, Francesco Nori, Martin A. Riedmiller, Nicolas Heess
2024	J	`jnl`	Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning. CoRR Dhruva Tirumala, Markus Wulfmeier, Ben Moran, Sandy H. Huang, Jan Humplik, Guy Lever, Tuomas Haarnoja, Leonard Hasenclever, Arunkumar Byravan, Nathan Batchelor, Neil Sreendra, Kushal Patel, Marlon Gwira, Francesco Nori, Martin A. Riedmiller, Nicolas Heess
2024	J	`jnl`	Learning agile soccer skills for a bipedal robot with deep reinforcement learning. Sci. Robotics Tuomas Haarnoja, Ben Moran, Guy Lever, Sandy H. Huang, Dhruva Tirumala, Jan Humplik, Markus Wulfmeier, Saran Tunyasuvunakool, Noah Y. Siegel, Roland Hafner, Michael Bloesch, Kristian Hartikainen, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, Nicolas Heess
2024	—	`conf`	Learning to Learn Faster from Human Feedback with Language Model Predictive Control. Robotics: Science and Systems Jacky Liang, Fei Xia, Wenhao Yu, Andy Zeng, Maria Attarian, Maria Bauzá Villalonga, Matthew Bennice, Alex Bewley, Adil Dostmohamed, Chuyuan Fu, Nimrod Gileadi, Marissa Giustina, Keerthana Gopalakrishnan, Leonard Hasenclever, Jan Humplik, Jasmine Hsu, Nikhil J. Joshi, Ben Jyenis, J. Chase Kew, Sean Kirmani, Tsang-Wei Edward Lee, Kuang-Huei Lee, Assaf Hurwitz Michaely, Joss Moore, Kenneth Oslund, Dushyant Rao, Allen Z. Ren, Baruch Tabanpour, Quan Vuong, Ayzaan Wahid, Ted Xiao, Ying Xu, Vincent Zhuang, Peng Xu, Erik Frey, Ken Caluwaerts, Tingnan Zhang, Brian Ichter, Jonathan Tompson, Leila Takayama, Vincent Vanhoucke, Izhak Shafran, Maja J. Mataric, Dorsa Sadigh, Nicolas Heess, Kanishka Rao, Nik Stewart, Jie Tan, Carolina Parada
2024	J	`jnl`	Learning to Learn Faster from Human Feedback with Language Model Predictive Control. CoRR Jacky Liang, Fei Xia, Wenhao Yu, Andy Zeng, Montserrat Gonzalez Arenas, Maria Attarian, Maria Bauzá, Matthew Bennice, Alex Bewley, Adil Dostmohamed, Chuyuan Kelly Fu, Nimrod Gileadi, Marissa Giustina, Keerthana Gopalakrishnan, Leonard Hasenclever, Jan Humplik, Jasmine Hsu, Nikhil J. Joshi, Ben Jyenis, J. Chase Kew, Sean Kirmani, Tsang-Wei Edward Lee, Kuang-Huei Lee, Assaf Hurwitz Michaely, Joss Moore, Ken Oslund, Dushyant Rao, Allen Z. Ren, Baruch Tabanpour, Quan Vuong, Ayzaan Wahid, Ted Xiao, Ying Xu, Vincent Zhuang, Peng Xu, Erik Frey, Ken Caluwaerts, Tingnan Zhang, Brian Ichter, Jonathan Tompson, Leila Takayama, Vincent Vanhoucke, Izhak Shafran, Maja J. Mataric, Dorsa Sadigh, Nicolas Heess, Kanishka Rao, Nik Stewart, Jie Tan, Carolina Parada
2024	A*	`conf`	Replay across Experiments: A Natural Extension of Off-Policy RL. ICLR Dhruva Tirumala, Thomas Lampe, José Enrique Chen, Tuomas Haarnoja, Sandy H. Huang, Guy Lever, Ben Moran, Tim Hertweck, Leonard Hasenclever, Martin A. Riedmiller, Nicolas Heess, Markus Wulfmeier
2023	J	`jnl`	A Generalist Dynamics Model for Control. CoRR Ingmar Schubert, Jingwei Zhang, Jake Bruce, Sarah Bechtle, Emilio Parisotto, Martin A. Riedmiller, Jost Tobias Springenberg, Arunkumar Byravan, Leonard Hasenclever, Nicolas Heess
2023	Misc	`conf`	Language to Rewards for Robotic Skill Synthesis. CoRL Wenhao Yu, Nimrod Gileadi, Chuyuan Fu, Sean Kirmani, Kuang-Huei Lee, Montserrat Gonzalez Arenas, Hao-Tien Lewis Chiang, Tom Erez, Leonard Hasenclever, Jan Humplik, Brian Ichter, Ted Xiao, Peng Xu, Andy Zeng, Tingnan Zhang, Nicolas Heess, Dorsa Sadigh, Jie Tan, Yuval Tassa, Fei Xia
2023	J	`jnl`	Language to Rewards for Robotic Skill Synthesis. CoRR Wenhao Yu, Nimrod Gileadi, Chuyuan Fu, Sean Kirmani, Kuang-Huei Lee, Montse Gonzalez Arenas, Hao-Tien Lewis Chiang, Tom Erez, Leonard Hasenclever, Jan Humplik, Brian Ichter, Ted Xiao, Peng Xu, Andy Zeng, Tingnan Zhang, Nicolas Heess, Dorsa Sadigh, Jie Tan, Yuval Tassa, Fei Xia
2023	J	`jnl`	Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning. CoRR Tuomas Haarnoja, Ben Moran, Guy Lever, Sandy H. Huang, Dhruva Tirumala, Markus Wulfmeier, Jan Humplik, Saran Tunyasuvunakool, Noah Y. Siegel, Roland Hafner, Michael Bloesch, Kristian Hartikainen, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, Nicolas Heess
2023	J	`jnl`	Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains. CoRR Jingwei Zhang, Jost Tobias Springenberg, Arunkumar Byravan, Leonard Hasenclever, Abbas Abdolmaleki, Dushyant Rao, Nicolas Heess, Martin A. Riedmiller
2023	A*	`conf`	NeRF2Real: Sim2real Transfer of Vision-guided Bipedal Motion Skills using Neural Radiance Fields. ICRA Arunkumar Byravan, Jan Humplik, Leonard Hasenclever, Arthur Brussee, Francesco Nori, Tuomas Haarnoja, Ben Moran, Steven Bohez, Fereshteh Sadeghi, Bojan Vujatovic, Nicolas Heess
2023	J	`jnl`	Replay across Experiments: A Natural Extension of Off-Policy RL. CoRR Dhruva Tirumala, Thomas Lampe, José Enrique Chen, Tuomas Haarnoja, Sandy H. Huang, Guy Lever, Ben Moran, Tim Hertweck, Leonard Hasenclever, Martin A. Riedmiller, Nicolas Heess, Markus Wulfmeier
2023	J	`jnl`	Towards A Unified Agent with Foundation Models. CoRR Norman Di Palo, Arunkumar Byravan, Leonard Hasenclever, Markus Wulfmeier, Nicolas Heess, Martin A. Riedmiller
2022	J	`jnl`	Behavior Priors for Efficient Reinforcement Learning. J. Mach. Learn. Res. Dhruva Tirumala, Alexandre Galashov, Hyeonwoo Noh, Leonard Hasenclever, Razvan Pascanu, Jonathan Schwarz, Guillaume Desjardins, Wojciech Marian Czarnecki, Arun Ahuja, Yee Whye Teh, Nicolas Heess
2022	A*	`conf`	Evaluating Model-Based Planning and Planner Amortization for Continuous Control. ICLR Arunkumar Byravan, Leonard Hasenclever, Piotr Trochim, Mehdi Mirza, Alessandro Davide Ialongo, Yuval Tassa, Jost Tobias Springenberg, Abbas Abdolmaleki, Nicolas Heess, Josh Merel, Martin A. Riedmiller
2022	J	`jnl`	From motor control to team play in simulated humanoid football. Sci. Robotics Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech M. Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess
2022	J	`jnl`	Imitate and Repurpose: Learning Reusable Robot Movement Skills From Human and Animal Behaviors. CoRR Steven Bohez, Saran Tunyasuvunakool, Philemon Brakel, Fereshteh Sadeghi, Leonard Hasenclever, Yuval Tassa, Emilio Parisotto, Jan Humplik, Tuomas Haarnoja, Roland Hafner, Markus Wulfmeier, Michael Neunert, Ben Moran, Noah Y. Siegel, Andrea Huber, Francesco Romano, Nathan Batchelor, Federico Casarini, Josh Merel, Raia Hadsell, Nicolas Heess
2022	A	`conf`	Learning Coordinated Terrain-Adaptive Locomotion by Imitating a Centroidal Dynamics Planner. IROS Philémon Brakel, Steven Bohez, Leonard Hasenclever, Nicolas Heess, Konstantinos Bousmalis
2022	A*	`conf`	Learning transferable motor skills with hierarchical latent mixture policies. ICLR Dushyant Rao, Fereshteh Sadeghi, Leonard Hasenclever, Markus Wulfmeier, Martina Zambelli, Giulia Vezzani, Dhruva Tirumala, Yusuf Aytar, Josh Merel, Nicolas Heess, Raia Hadsell
2022	J	`jnl`	NeRF2Real: Sim2real Transfer of Vision-guided Bipedal Motion Skills using Neural Radiance Fields. CoRR Arunkumar Byravan, Jan Humplik, Leonard Hasenclever, Arthur Brussee, Francesco Nori, Tuomas Haarnoja, Ben Moran, Steven Bohez, Fereshteh Sadeghi, Bojan Vujatovic, Nicolas Heess
2021	J	`jnl`	Evaluating model-based planning and planner amortization for continuous control. CoRR Arunkumar Byravan, Leonard Hasenclever, Piotr Trochim, Mehdi Mirza, Alessandro Davide Ialongo, Yuval Tassa, Jost Tobias Springenberg, Abbas Abdolmaleki, Nicolas Heess, Josh Merel, Martin A. Riedmiller
2021	J	`jnl`	From Motor Control to Team Play in Simulated Humanoid Football. CoRR Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech M. Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess
2021	J	`jnl`	Learning Coordinated Terrain-Adaptive Locomotion by Imitating a Centroidal Dynamics Planner. CoRR Philemon Brakel, Steven Bohez, Leonard Hasenclever, Nicolas Heess, Konstantinos Bousmalis
2021	J	`jnl`	Learning Dynamics Models for Model Predictive Agents. CoRR Michael Lutter, Leonard Hasenclever, Arunkumar Byravan, Gabriel Dulac-Arnold, Piotr Trochim, Nicolas Heess, Josh Merel, Yuval Tassa
2021	J	`jnl`	Learning Transferable Motor Skills with Hierarchical Latent Mixture Policies. CoRR Dushyant Rao, Fereshteh Sadeghi, Leonard Hasenclever, Markus Wulfmeier, Martina Zambelli, Giulia Vezzani, Dhruva Tirumala, Yusuf Aytar, Josh Merel, Nicolas Heess, Raia Hadsell
2020	J	`jnl`	A Distributional View on Multi-Objective Policy Optimization. CoRR Abbas Abdolmaleki, Sandy H. Huang, Leonard Hasenclever, Michael Neunert, H. Francis Song, Martina Zambelli, Murilo F. Martins, Nicolas Heess, Raia Hadsell, Martin A. Riedmiller
2020	A*	`conf`	A distributional view on multi-objective policy optimization. ICML Abbas Abdolmaleki, Sandy H. Huang, Leonard Hasenclever, Michael Neunert, H. Francis Song, Martina Zambelli, Murilo F. Martins, Nicolas Heess, Raia Hadsell, Martin A. Riedmiller
2020	J	`jnl`	Behavior Priors for Efficient Reinforcement Learning. CoRR Dhruva Tirumala, Alexandre Galashov, Hyeonwoo Noh, Leonard Hasenclever, Razvan Pascanu, Jonathan Schwarz, Guillaume Desjardins, Wojciech Marian Czarnecki, Arun Ahuja, Yee Whye Teh, Nicolas Heess
2020	J	`jnl`	Catch & Carry: reusable neural controllers for vision-guided whole-body tasks. ACM Trans. Graph. Josh Merel, Saran Tunyasuvunakool, Arun Ahuja, Yuval Tassa, Leonard Hasenclever, Vu Pham, Tom Erez, Greg Wayne, Nicolas Heess
2020	A*	`conf`	CoMic: Complementary Task Learning & Mimicry for Reusable Skills. ICML Leonard Hasenclever, Fabio Pardo, Raia Hadsell, Nicolas Heess, Josh Merel
2020	J	`jnl`	Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning. CoRR Giambattista Parascandolo, Lars Buesing, Josh Merel, Leonard Hasenclever, John Aslanides, Jessica B. Hamrick, Nicolas Heess, Alexander Neitz, Theophane Weber
2020	J	`jnl`	Importance Weighted Policy Learning and Adaption. CoRR Alexandre Galashov, Jakub Sygnowski, Guillaume Desjardins, Jan Humplik, Leonard Hasenclever, Rae Jeong, Yee Whye Teh, Nicolas Heess
2019	J	`jnl`	Exploiting Hierarchy for Learning and Transfer in KL-regularized RL. CoRR Dhruva Tirumala, Hyeonwoo Noh, Alexandre Galashov, Leonard Hasenclever, Arun Ahuja, Greg Wayne, Razvan Pascanu, Yee Whye Teh, Nicolas Heess
2019	—	`conf`	Information asymmetry in KL-regularized RL. ICLR (Poster) Alexandre Galashov, Siddhant M. Jayakumar, Leonard Hasenclever, Dhruva Tirumala, Jonathan Schwarz, Guillaume Desjardins, Wojciech M. Czarnecki, Yee Whye Teh, Razvan Pascanu, Nicolas Heess
2019	J	`jnl`	Information asymmetry in KL-regularized RL. CoRR Alexandre Galashov, Siddhant M. Jayakumar, Leonard Hasenclever, Dhruva Tirumala, Jonathan Schwarz, Guillaume Desjardins, Wojciech M. Czarnecki, Yee Whye Teh, Razvan Pascanu, Nicolas Heess
2019	J	`jnl`	Meta reinforcement learning as task inference. CoRR Jan Humplik, Alexandre Galashov, Leonard Hasenclever, Pedro A. Ortega, Yee Whye Teh, Nicolas Heess
2019	—	`conf`	Neural Probabilistic Motor Primitives for Humanoid Control. ICLR (Poster) Josh Merel, Leonard Hasenclever, Alexandre Galashov, Arun Ahuja, Vu Pham, Greg Wayne, Yee Whye Teh, Nicolas Heess
2019	A	`conf`	Observational Learning by Reinforcement Learning. AAMAS Diana Borsa, Nicolas Heess, Bilal Piot, Siqi Liu, Leonard Hasenclever, Rémi Munos, Olivier Pietquin
2019	J	`jnl`	Reusable neural skill embeddings for vision-guided whole body movement and object manipulation. CoRR Josh Merel, Saran Tunyasuvunakool, Arun Ahuja, Yuval Tassa, Leonard Hasenclever, Vu Pham, Tom Erez, Greg Wayne, Nicolas Heess
2018	A*	`conf`	Mix & Match Agent Curricula for Reinforcement Learning. ICML Wojciech Marian Czarnecki, Siddhant M. Jayakumar, Max Jaderberg, Leonard Hasenclever, Yee Whye Teh, Nicolas Heess, Simon Osindero, Razvan Pascanu
2018	J	`jnl`	Mix&Match - Agent Curricula for Reinforcement Learning. CoRR Wojciech Marian Czarnecki, Siddhant M. Jayakumar, Max Jaderberg, Leonard Hasenclever, Yee Whye Teh, Simon Osindero, Nicolas Heess, Razvan Pascanu
2018	J	`jnl`	Neural probabilistic motor primitives for humanoid control. CoRR Josh Merel, Leonard Hasenclever, Alexandre Galashov, Arun Ahuja, Vu Pham, Greg Wayne, Yee Whye Teh, Nicolas Heess
2018	—	`—`	Probabilistic machine learning: methods and applications to continuous control. Leonard Hasenclever
2018	A	`conf`	Sylvester Normalizing Flows for Variational Inference. UAI Rianne van den Berg, Leonard Hasenclever, Jakub M. Tomczak, Max Welling
2018	J	`jnl`	Sylvester Normalizing Flows for Variational Inference. CoRR Rianne van den Berg, Leonard Hasenclever, Jakub M. Tomczak, Max Welling
2017	J	`jnl`	Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server. J. Mach. Learn. Res. Leonard Hasenclever, Stefan Webb, Thibaut Liénart, Sebastian J. Vollmer, Balaji Lakshminarayanan, Charles Blundell, Yee Whye Teh
2017	A	`conf`	Relativistic Monte Carlo. AISTATS Xiaoyu Lu, Valerio Perrone, Leonard Hasenclever, Yee Whye Teh, Sebastian J. Vollmer
2015	J	`jnl`	Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server. CoRR Yee Whye Teh, Leonard Hasenclever, Thibaut Liénart, Sebastian J. Vollmer, Stefan Webb, Balaji Lakshminarayanan, Charles Blundell
2014	J	`jnl`	An investigation into irreducible autocatalytic sets and power law distributed catalysis. Nat. Comput. Wim Hordijk, Leonard Hasenclever, Jie Gao, Dilyana Mincheva, Jotun Hein