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ORCIDJosh Merel
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- affiliation: Google DeepMind, London, UK
- affiliation: Columbia University, Department of Neurobiology and Behavior, New York, NY, USA
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2020 – today
- 2024
[c21]Zhengyi Luo, Jinkun Cao, Josh Merel, Alexander Winkler, Jing Huang, Kris M. Kitani, Weipeng Xu:
Universal Humanoid Motion Representations for Physics-Based Control. ICLR 2024- [i27]Yusheng Jiao, Feng Ling, Sina Heydari
, Nicolas Heess, Josh Merel, Eva Kanso:
Deep Dive into Model-free Reinforcement Learning for Biological and Robotic Systems: Theory and Practice. CoRR abs/2405.11457 (2024) - 2023
- [i26]Zhengyi Luo, Jinkun Cao, Josh Merel, Alexander Winkler, Jing Huang, Kris Kitani, Weipeng Xu:
Universal Humanoid Motion Representations for Physics-Based Control. CoRR abs/2310.04582 (2023) - 2022
- [j5]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) - [c20]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 - [c19]Siqi Liu, Luke Marris, Daniel Hennes, Josh Merel, Nicolas Heess, Thore Graepel:
NeuPL: Neural Population Learning. ICLR 2022 - [c18]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 - [c17]Alexandre Galashov, Joshua Scott Merel, Nicolas Heess:
Data augmentation for efficient learning from parametric experts. NeurIPS 2022 - [d1]Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech 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:
Figure Data for the paper "From Motor Control to Team Play in Simulated Humanoid Football". Zenodo, 2022
- [i25]Siqi Liu, Luke Marris, Daniel Hennes, Josh Merel, Nicolas Heess, Thore Graepel:
NeuPL: Neural Population Learning. CoRR abs/2202.07415 (2022) - [i24]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 abs/2203.17138 (2022) - [i23]Alexandre Galashov, Josh Merel, Nicolas Heess:
Data augmentation for efficient learning from parametric experts. CoRR abs/2205.11448 (2022) - 2021
- [c16]Vittorio Caggiano, Guillaume Durandau, Huawei Wang, Alberto Silvio Chiappa, Alexander Mathis, Pablo Tano, Nisheet Patel, Alexandre Pouget, Pierre Schumacher, Georg Martius, Daniel F. B. Haeufle, Yiran Geng, Boshi An, Yifan Zhong, Jiaming Ji, Yuanpei Chen, Hao Dong, Yaodong Yang, Rahul Siripurapu, Luis Eduardo Ferro Diez, Michael Kopp, Vihang Patil, Sepp Hochreiter, Yuval Tassa, Josh Merel, Randy Schultheis, Seungmoon Song, Massimo Sartori, Vikash Kumar:
MyoChallenge 2022: Learning contact-rich manipulation using a musculoskeletal hand. NeurIPS (Competition and Demos) 2021: 233-250 - [i22]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 abs/2105.12196 (2021) - [i21]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 abs/2109.14311 (2021) - [i20]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 abs/2110.03363 (2021) - [i19]Grace W. Lindsay, Josh Merel, Tom Mrsic-Flogel, Maneesh Sahani:
Divergent representations of ethological visual inputs emerge from supervised, unsupervised, and reinforcement learning. CoRR abs/2112.02027 (2021) - [i18]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 abs/2112.05062 (2021) - 2020
- [j4]Saran Tunyasuvunakool, Alistair Muldal, Yotam Doron, Siqi Liu, Steven Bohez, Josh Merel, Tom Erez, Timothy P. Lillicrap, Nicolas Heess, Yuval Tassa:
dm_control: Software and tasks for continuous control. Softw. Impacts 6: 100022 (2020) - [j3]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): 39 (2020) - [c15]Josh Merel, Diego Aldarondo, Jesse Marshall, Yuval Tassa, Greg Wayne, Bence Olveczky:
Deep neuroethology of a virtual rodent. ICLR 2020 - [c14]Leonard Hasenclever, Fabio Pardo, Raia Hadsell, Nicolas Heess, Josh Merel:
CoMic: Complementary Task Learning & Mimicry for Reusable Skills. ICML 2020: 4105-4115 - [c13]Ziyu Wang, Alexander Novikov, Konrad Zolna, Josh Merel, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas:
Critic Regularized Regression. NeurIPS 2020 - [c12]Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Thomas Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matthew Hoffman, Nicolas Heess, Nando de Freitas:
RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning. NeurIPS 2020 - [i17]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 abs/2004.11410 (2020) - [i16]Yuval Tassa, Saran Tunyasuvunakool, Alistair Muldal, Yotam Doron, Siqi Liu, Steven Bohez, Josh Merel, Tom Erez, Timothy P. Lillicrap, Nicolas Heess:
dm_control: Software and Tasks for Continuous Control. CoRR abs/2006.12983 (2020) - [i15]Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Tom Le Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, George Tucker, Nicolas Heess, Nando de Freitas:
RL Unplugged: Benchmarks for Offline Reinforcement Learning. CoRR abs/2006.13888 (2020) - [i14]Ziyu Wang, Alexander Novikov, Konrad Zolna, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Josh Merel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas:
Critic Regularized Regression. CoRR abs/2006.15134 (2020) - [i13]Yusheng Jiao, Feng Ling, Sina Heydari, Nicolas Heess, Josh Merel, Eva Kanso:
Learning to swim in potential flow. CoRR abs/2009.14280 (2020) - [i12]Jost Tobias Springenberg, Nicolas Heess, Daniel J. Mankowitz, Josh Merel, Arunkumar Byravan, Abbas Abdolmaleki, Jackie Kay, Jonas Degrave, Julian Schrittwieser, Yuval Tassa, Jonas Buchli, Dan Belov, Martin A. Riedmiller:
Local Search for Policy Iteration in Continuous Control. CoRR abs/2010.05545 (2020)
2010 – 2019
- 2019
- [c11]Siqi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, Thore Graepel:
Emergent Coordination Through Competition. ICLR (Poster) 2019 - [c10]Josh Merel, Arun Ahuja, Vu Pham, Saran Tunyasuvunakool, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Greg Wayne:
Hierarchical Visuomotor Control of Humanoids. ICLR (Poster) 2019 - [c9]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 - [c8]Peter Sunehag, Guy Lever, Siqi Liu, Josh Merel, Nicolas Heess, Joel Z. Leibo, Edward Hughes, Tom Eccles, Thore Graepel:
Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems. ALIFE 2019: 103-110 - [i11]Siqi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, Thore Graepel:
Emergent Coordination Through Competition. CoRR abs/1902.07151 (2019) - [i10]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 abs/1911.06636 (2019) - 2018
- [c7]Alvaro Sanchez-Gonzalez, Nicolas Heess, Jost Tobias Springenberg, Josh Merel, Martin A. Riedmiller, Raia Hadsell, Peter W. Battaglia:
Graph Networks as Learnable Physics Engines for Inference and Control. ICML 2018: 4467-4476 - [c6]Yuke Zhu, Ziyu Wang, Josh Merel, Andrei A. Rusu, Tom Erez, Serkan Cabi, Saran Tunyasuvunakool, János Kramár, Raia Hadsell, Nando de Freitas, Nicolas Heess:
Reinforcement and Imitation Learning for Diverse Visuomotor Skills. Robotics: Science and Systems 2018 - [i9]Yuval Tassa, Yotam Doron, Alistair Muldal, Tom Erez, Yazhe Li, Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, Timothy P. Lillicrap, Martin A. Riedmiller:
DeepMind Control Suite. CoRR abs/1801.00690 (2018) - [i8]Yuke Zhu, Ziyu Wang, Josh Merel, Andrei A. Rusu, Tom Erez, Serkan Cabi, Saran Tunyasuvunakool, János Kramár, Raia Hadsell, Nando de Freitas, Nicolas Heess:
Reinforcement and Imitation Learning for Diverse Visuomotor Skills. CoRR abs/1802.09564 (2018) - [i7]Alvaro Sanchez-Gonzalez, Nicolas Heess, Jost Tobias Springenberg, Josh Merel, Martin A. Riedmiller, Raia Hadsell, Peter W. Battaglia:
Graph networks as learnable physics engines for inference and control. CoRR abs/1806.01242 (2018) - [i6]Josh Merel, Arun Ahuja, Vu Pham, Saran Tunyasuvunakool, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Greg Wayne:
Hierarchical visuomotor control of humanoids. CoRR abs/1811.09656 (2018) - [i5]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 abs/1811.11711 (2018) - 2017
- [c5]Eleanor Batty, Josh Merel, Nora Brackbill, Alexander Heitman, Alexander Sher, Alan M. Litke, E. J. Chichilnisky, Liam Paninski:
Multilayer Recurrent Network Models of Primate Retinal Ganglion Cell Responses. ICLR (Poster) 2017 - [c4]Ziyu Wang, Josh Merel, Scott E. Reed, Nando de Freitas, Gregory Wayne, Nicolas Heess:
Robust Imitation of Diverse Behaviors. NIPS 2017: 5320-5329 - [i4]Josh Merel, Yuval Tassa, Dhruva TB, Sriram Srinivasan, Jay Lemmon, Ziyu Wang, Greg Wayne, Nicolas Heess:
Learning human behaviors from motion capture by adversarial imitation. CoRR abs/1707.02201 (2017) - [i3]Nicolas Heess, Dhruva TB, Srinivasan Sriram, Jay Lemmon, Josh Merel, Greg Wayne, Yuval Tassa, Tom Erez, Ziyu Wang, S. M. Ali Eslami, Martin A. Riedmiller, David Silver:
Emergence of Locomotion Behaviours in Rich Environments. CoRR abs/1707.02286 (2017) - [i2]Ziyu Wang, Josh Merel, Scott E. Reed, Greg Wayne, Nando de Freitas, Nicolas Heess:
Robust Imitation of Diverse Behaviors. CoRR abs/1707.02747 (2017) - 2016
- [b1]Joshua Scott Merel:
New perspectives on learning, inference, and control in brains and machines. Columbia University, USA, 2016 - [j2]Josh Merel, David E. Carlson, Liam Paninski, John P. Cunningham:
Neuroprosthetic Decoder Training as Imitation Learning. PLoS Comput. Biol. 12(5) (2016) - 2015
- [j1]Josh Merel, Donald M. Pianto, John P. Cunningham, Liam Paninski:
Encoder-Decoder Optimization for Brain-Computer Interfaces. PLoS Comput. Biol. 11(6) (2015) - [i1]Josh Merel, David E. Carlson, Liam Paninski, John P. Cunningham:
Neuroprosthetic decoder training as imitation learning. CoRR abs/1511.04156 (2015) - 2013
- [c3]Eftychios A. Pnevmatikakis, Josh Merel, Ari Pakman, Liam Paninski:
Bayesian spike inference from calcium imaging data. ACSSC 2013: 349-353 - [c2]Josh Merel, Roy Fox, Tony Jebara, Liam Paninski:
A multi-agent control framework for co-adaptation in brain-computer interfaces. NIPS 2013: 2841-2849 - 2012
- [c1]Yan Tat Wong, Mariana Vigeral, David Putrino, David Pfau, Josh Merel, Liam Paninski, Bijan Pesaran:
Decoding arm and hand movements across layers of the macaque frontal cortices. EMBC 2012: 1757-1760
Coauthor Index
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last updated on 2024-10-21 21:27 CEST by the dblp team
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