Leonard Hasenclever

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 46

Top Topics

Expectation Propagation

Reinforcement Learning

Top Venues

Publications

Norman Di Palo, Leonard Hasenclever, Jan Humplik, Arunkumar Byravan
Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning. CoRR (2024)
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
Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning. CoRR (2024)
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
Replay across Experiments: A Natural Extension of Off-Policy RL. ICLR (2024)
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
Learning to Learn Faster from Human Feedback with Language Model Predictive Control. CoRR (2024)
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
Learning agile soccer skills for a bipedal robot with deep reinforcement learning. Sci. Robotics 9 (89) (2024)
Ingmar Schubert, Jingwei Zhang, Jake Bruce, Sarah Bechtle, Emilio Parisotto, Martin A. Riedmiller, Jost Tobias Springenberg, Arunkumar Byravan, Leonard Hasenclever, Nicolas Heess
A Generalist Dynamics Model for Control. CoRR (2023)
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
Language to Rewards for Robotic Skill Synthesis. CoRL (2023)
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
Language to Rewards for Robotic Skill Synthesis. CoRR (2023)
Arunkumar Byravan, Jan Humplik, Leonard Hasenclever, Arthur Brussee, Francesco Nori, Tuomas Haarnoja, Ben Moran, Steven Bohez, Fereshteh Sadeghi, Bojan Vujatovic, Nicolas Heess
NeRF2Real: Sim2real Transfer of Vision-guided Bipedal Motion Skills using Neural Radiance Fields. ICRA (2023)
Norman Di Palo, Arunkumar Byravan, Leonard Hasenclever, Markus Wulfmeier, Nicolas Heess, Martin A. Riedmiller
Towards A Unified Agent with Foundation Models. CoRR (2023)
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
Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning. CoRR (2023)
Dhruva Tirumala, Thomas Lampe, Jose Enrique Chen, Tuomas Haarnoja, Sandy H. Huang, Guy Lever, Ben Moran, Tim Hertweck, Leonard Hasenclever, Martin A. Riedmiller, Nicolas Heess, Markus Wulfmeier
Replay across Experiments: A Natural Extension of Off-Policy RL. CoRR (2023)
Jingwei Zhang, Jost Tobias Springenberg, Arunkumar Byravan, Leonard Hasenclever, Abbas Abdolmaleki, Dushyant Rao, Nicolas Heess, Martin A. Riedmiller
Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains. CoRR (2023)
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
Evaluating Model-Based Planning and Planner Amortization for Continuous Control. ICLR (2022)
Arunkumar Byravan, Jan Humplik, Leonard Hasenclever, Arthur Brussee, Francesco Nori, Tuomas Haarnoja, Ben Moran, Steven Bohez, Fereshteh Sadeghi, Bojan Vujatovic, Nicolas Heess
NeRF2Real: Sim2real Transfer of Vision-guided Bipedal Motion Skills using Neural Radiance Fields. CoRR (2022)
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
From motor control to team play in simulated humanoid football. Sci. Robotics 7 (69) (2022)
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
Imitate and Repurpose: Learning Reusable Robot Movement Skills From Human and Animal Behaviors. CoRR (2022)
Dushyant Rao, Fereshteh Sadeghi, Leonard Hasenclever, Markus Wulfmeier, Martina Zambelli, Giulia Vezzani, Dhruva Tirumala, Yusuf Aytar, Josh Merel, Nicolas Heess, Raia Hadsell
Learning transferable motor skills with hierarchical latent mixture policies. ICLR (2022)
Philémon Brakel, Steven Bohez, Leonard Hasenclever, Nicolas Heess, Konstantinos Bousmalis
Learning Coordinated Terrain-Adaptive Locomotion by Imitating a Centroidal Dynamics Planner. IROS (2022)
Dhruva Tirumala, Alexandre Galashov, Hyeonwoo Noh, Leonard Hasenclever, Razvan Pascanu, Jonathan Schwarz, Guillaume Desjardins, Wojciech Marian Czarnecki, Arun Ahuja, Yee Whye Teh, Nicolas Heess
Behavior Priors for Efficient Reinforcement Learning. J. Mach. Learn. Res. 23 (2022)
Michael Lutter, Leonard Hasenclever, Arunkumar Byravan, Gabriel Dulac-Arnold, Piotr Trochim, Nicolas Heess, Josh Merel, Yuval Tassa
Learning Dynamics Models for Model Predictive Agents. CoRR (2021)
Philemon Brakel, Steven Bohez, Leonard Hasenclever, Nicolas Heess, Konstantinos Bousmalis
Learning Coordinated Terrain-Adaptive Locomotion by Imitating a Centroidal Dynamics Planner. CoRR (2021)
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
Evaluating model-based planning and planner amortization for continuous control. CoRR (2021)
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
From Motor Control to Team Play in Simulated Humanoid Football. CoRR (2021)
Dushyant Rao, Fereshteh Sadeghi, Leonard Hasenclever, Markus Wulfmeier, Martina Zambelli, Giulia Vezzani, Dhruva Tirumala, Yusuf Aytar, Josh Merel, Nicolas Heess, Raia Hadsell
Learning Transferable Motor Skills with Hierarchical Latent Mixture Policies. CoRR (2021)
Abbas Abdolmaleki, Sandy H. Huang, Leonard Hasenclever, Michael Neunert, H. Francis Song, Martina Zambelli, Murilo F. Martins, Nicolas Heess, Raia Hadsell, Martin A. Riedmiller
A Distributional View on Multi-Objective Policy Optimization. CoRR (2020)
Leonard Hasenclever, Fabio Pardo, Raia Hadsell, Nicolas Heess, Josh Merel
CoMic: Complementary Task Learning & Mimicry for Reusable Skills. ICML (2020)
Josh Merel, Saran Tunyasuvunakool, Arun Ahuja, Yuval Tassa, Leonard Hasenclever, Vu Pham, Tom Erez, Greg Wayne, Nicolas Heess
Catch & Carry: reusable neural controllers for vision-guided whole-body tasks. ACM Trans. Graph. 39 (4) (2020)
Dhruva Tirumala, Alexandre Galashov, Hyeonwoo Noh, Leonard Hasenclever, Razvan Pascanu, Jonathan Schwarz, Guillaume Desjardins, Wojciech Marian Czarnecki, Arun Ahuja, Yee Whye Teh, Nicolas Heess
Behavior Priors for Efficient Reinforcement Learning. CoRR (2020)
Giambattista Parascandolo, Lars Buesing, Josh Merel, Leonard Hasenclever, John Aslanides, Jessica B. Hamrick, Nicolas Heess, Alexander Neitz, Theophane Weber
Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning. CoRR (2020)
Abbas Abdolmaleki, Sandy H. Huang, Leonard Hasenclever, Michael Neunert, H. Francis Song, Martina Zambelli, Murilo F. Martins, Nicolas Heess, Raia Hadsell, Martin A. Riedmiller
A distributional view on multi-objective policy optimization. ICML (2020)
Alexandre Galashov, Jakub Sygnowski, Guillaume Desjardins, Jan Humplik, Leonard Hasenclever, Rae Jeong, Yee Whye Teh, Nicolas Heess
Importance Weighted Policy Learning and Adaption. CoRR (2020)
Diana Borsa, Nicolas Heess, Bilal Piot, Siqi Liu, Leonard Hasenclever, Rémi Munos, Olivier Pietquin
Observational Learning by Reinforcement Learning. AAMAS (2019)
Josh Merel, Saran Tunyasuvunakool, Arun Ahuja, Yuval Tassa, Leonard Hasenclever, Vu Pham, Tom Erez, Greg Wayne, Nicolas Heess
Reusable neural skill embeddings for vision-guided whole body movement and object manipulation. CoRR (2019)
Alexandre Galashov, Siddhant M. Jayakumar, Leonard Hasenclever, Dhruva Tirumala, Jonathan Schwarz, Guillaume Desjardins, Wojciech M. Czarnecki, Yee Whye Teh, Razvan Pascanu, Nicolas Heess
Information asymmetry in KL-regularized RL. CoRR (2019)
Alexandre Galashov, Siddhant M. Jayakumar, Leonard Hasenclever, Dhruva Tirumala, Jonathan Schwarz, Guillaume Desjardins, Wojciech M. Czarnecki, Yee Whye Teh, Razvan Pascanu, Nicolas Heess
Information asymmetry in KL-regularized RL. ICLR (Poster) (2019)
Jan Humplik, Alexandre Galashov, Leonard Hasenclever, Pedro A. Ortega, Yee Whye Teh, Nicolas Heess
Meta reinforcement learning as task inference. CoRR (2019)
Josh Merel, Leonard Hasenclever, Alexandre Galashov, Arun Ahuja, Vu Pham, Greg Wayne, Yee Whye Teh, Nicolas Heess
Neural Probabilistic Motor Primitives for Humanoid Control. ICLR (Poster) (2019)
Dhruva Tirumala, Hyeonwoo Noh, Alexandre Galashov, Leonard Hasenclever, Arun Ahuja, Greg Wayne, Razvan Pascanu, Yee Whye Teh, Nicolas Heess
Exploiting Hierarchy for Learning and Transfer in KL-regularized RL. CoRR (2019)
Rianne van den Berg, Leonard Hasenclever, Jakub M. Tomczak, Max Welling
Sylvester Normalizing Flows for Variational Inference. CoRR (2018)
Wojciech Marian Czarnecki, Siddhant M. Jayakumar, Max Jaderberg, Leonard Hasenclever, Yee Whye Teh, Nicolas Heess, Simon Osindero, Razvan Pascanu
Mix & Match Agent Curricula for Reinforcement Learning. ICML (2018)
Josh Merel, Leonard Hasenclever, Alexandre Galashov, Arun Ahuja, Vu Pham, Greg Wayne, Yee Whye Teh, Nicolas Heess
Neural probabilistic motor primitives for humanoid control. CoRR (2018)
Rianne van den Berg, Leonard Hasenclever, Jakub M. Tomczak, Max Welling
Sylvester Normalizing Flows for Variational Inference. UAI (2018)
Wojciech Marian Czarnecki, Siddhant M. Jayakumar, Max Jaderberg, Leonard Hasenclever, Yee Whye Teh, Simon Osindero, Nicolas Heess, Razvan Pascanu
Mix&Match - Agent Curricula for Reinforcement Learning. CoRR (2018)
Xiaoyu Lu, Valerio Perrone, Leonard Hasenclever, Yee Whye Teh, Sebastian J. Vollmer
Relativistic Monte Carlo. AISTATS (2017)
Leonard Hasenclever, Stefan Webb, Thibaut Lienart, Sebastian J. Vollmer, Balaji Lakshminarayanan, Charles Blundell, Yee Whye Teh
Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server. J. Mach. Learn. Res. 18 (2017)
Yee Whye Teh, Leonard Hasenclever, Thibaut Lienart, Sebastian J. Vollmer, Stefan Webb, Balaji Lakshminarayanan, Charles Blundell
Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server. CoRR (2015)
Wim Hordijk, Leonard Hasenclever, Jie Gao, Dilyana Mincheva, Jotun Hein
An investigation into irreducible autocatalytic sets and power law distributed catalysis. Nat. Comput. 13 (3) (2014)