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Yuval Tassa
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2020 – today
- 2024
- [j5]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) - 2023
- [c26]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: 374-404 - [c25]Kevin Zakka, Philipp Wu, Laura M. Smith, Nimrod Gileadi, Taylor Howell, Xue Bin Peng, Sumeet Singh, Yuval Tassa, Pete Florence, Andy Zeng, Pieter Abbeel:
RoboPianist: Dexterous Piano Playing with Deep Reinforcement Learning. CoRL 2023: 2975-2994 - [i26]Kevin Zakka, Laura M. Smith, Nimrod Gileadi, Taylor A. Howell, Xue Bin Peng, Sumeet Singh, Yuval Tassa, Pete Florence, Andy Zeng, Pieter Abbeel:
RoboPianist: A Benchmark for High-Dimensional Robot Control. CoRR abs/2304.04150 (2023) - [i25]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 abs/2304.13653 (2023) - [i24]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 abs/2306.08647 (2023) - [i23]Kevin Tracy, Zachary Manchester, Ajinkya Jain, Keegan Go, Stefan Schaal, Tom Erez, Yuval Tassa:
Efficient Online Learning of Contact Force Models for Connector Insertion. CoRR abs/2312.09190 (2023) - 2022
- [j4]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) - [c24]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 - [i22]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) - [i21]Taylor Howell, Nimrod Gileadi, Saran Tunyasuvunakool, Kevin Zakka, Tom Erez, Yuval Tassa:
Predictive Sampling: Real-time Behaviour Synthesis with MuJoCo. CoRR abs/2212.00541 (2022) - 2021
- [c23]Sandy H. Huang, Abbas Abdolmaleki, Giulia Vezzani, Philemon Brakel, Daniel J. Mankowitz, Michael Neunert, Steven Bohez, Yuval Tassa, Nicolas Heess, Martin A. Riedmiller, Raia Hadsell:
A Constrained Multi-Objective Reinforcement Learning Framework. CoRL 2021: 883-893 - [c22]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 - [i20]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) - [i19]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) - [i18]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) - [i17]Vittorio La Barbera, Fabio Pardo, Yuval Tassa, Monica Daley, Christopher Richards, Petar Kormushev, John Hutchinson:
OstrichRL: A Musculoskeletal Ostrich Simulation to Study Bio-mechanical Locomotion. CoRR abs/2112.06061 (2021) - 2020
- [j3]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) - [j2]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) - [c21]Josh Merel, Diego Aldarondo, Jesse Marshall, Yuval Tassa, Greg Wayne, Bence Olveczky:
Deep neuroethology of a virtual rodent. ICLR 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]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
- [i14]Sandy H. Huang, Martina Zambelli, Jackie Kay, Murilo F. Martins, Yuval Tassa, Patrick M. Pilarski, Raia Hadsell:
Learning Gentle Object Manipulation with Curiosity-Driven Deep Reinforcement Learning. CoRR abs/1903.08542 (2019) - [i13]Rae Jeong, Jackie Kay, Francesco Romano, Thomas Lampe, Thomas Rothörl, Abbas Abdolmaleki, Tom Erez, Yuval Tassa, Francesco Nori:
Modelling Generalized Forces with Reinforcement Learning for Sim-to-Real Transfer. CoRR abs/1910.09471 (2019) - [i12]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
- [c20]Abbas Abdolmaleki, Jost Tobias Springenberg, Yuval Tassa, Rémi Munos, Nicolas Heess, Martin A. Riedmiller:
Maximum a Posteriori Policy Optimisation. ICLR (Poster) 2018 - [c19]Brandon Amos, Laurent Dinh, Serkan Cabi, Thomas Rothörl, Sergio Gomez Colmenarejo, Alistair Muldal, Tom Erez, Yuval Tassa, Nando de Freitas, Misha Denil:
Learning Awareness Models. ICLR (Poster) 2018 - [i11]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) - [i10]Gal Dalal, Krishnamurthy Dvijotham, Matej Vecerík, Todd Hester, Cosmin Paduraru, Yuval Tassa:
Safe Exploration in Continuous Action Spaces. CoRR abs/1801.08757 (2018) - [i9]Brandon Amos, Laurent Dinh, Serkan Cabi, Thomas Rothörl, Sergio Gomez Colmenarejo, Alistair Muldal, Tom Erez, Yuval Tassa, Nando de Freitas, Misha Denil:
Learning Awareness Models. CoRR abs/1804.06318 (2018) - [i8]Abbas Abdolmaleki, Jost Tobias Springenberg, Yuval Tassa, Rémi Munos, Nicolas Heess, Martin A. Riedmiller:
Maximum a Posteriori Policy Optimisation. CoRR abs/1806.06920 (2018) - [i7]Abbas Abdolmaleki, Jost Tobias Springenberg, Jonas Degrave, Steven Bohez, Yuval Tassa, Dan Belov, Nicolas Heess, Martin A. Riedmiller:
Relative Entropy Regularized Policy Iteration. CoRR abs/1812.02256 (2018) - 2017
- [i6]Ivaylo Popov, Nicolas Heess, Timothy P. Lillicrap, Roland Hafner, Gabriel Barth-Maron, Matej Vecerík, Thomas Lampe, Yuval Tassa, Tom Erez, Martin A. Riedmiller:
Data-efficient Deep Reinforcement Learning for Dexterous Manipulation. CoRR abs/1704.03073 (2017) - [i5]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) - [i4]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) - 2016
- [c18]S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, Koray Kavukcuoglu, Geoffrey E. Hinton:
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models. NIPS 2016: 3225-3233 - [c17]Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, Daan Wierstra:
Continuous control with deep reinforcement learning. ICLR (Poster) 2016 - [i3]S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, Koray Kavukcuoglu, Geoffrey E. Hinton:
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models. CoRR abs/1603.08575 (2016) - [i2]Nicolas Heess, Gregory Wayne, Yuval Tassa, Timothy P. Lillicrap, Martin A. Riedmiller, David Silver:
Learning and Transfer of Modulated Locomotor Controllers. CoRR abs/1610.05182 (2016) - 2015
- [c16]Tom Erez, Yuval Tassa, Emanuel Todorov:
Simulation tools for model-based robotics: Comparison of Bullet, Havok, MuJoCo, ODE and PhysX. ICRA 2015: 4397-4404 - [c15]Jonas Koenemann, Andrea Del Prete
, Yuval Tassa, Emanuel Todorov, Olivier Stasse
, Maren Bennewitz, Nicolas Mansard:
Whole-body model-predictive control applied to the HRP-2 humanoid. IROS 2015: 3346-3351 - [c14]Nicolas Heess, Gregory Wayne, David Silver, Timothy P. Lillicrap, Tom Erez, Yuval Tassa:
Learning Continuous Control Policies by Stochastic Value Gradients. NIPS 2015: 2944-2952 - [i1]Nicolas Heess, Greg Wayne, David Silver, Timothy P. Lillicrap, Yuval Tassa, Tom Erez:
Learning Continuous Control Policies by Stochastic Value Gradients. CoRR abs/1510.09142 (2015) - 2014
- [c13]Yuval Tassa, Nicolas Mansard, Emo Todorov:
Control-limited differential dynamic programming. ICRA 2014: 1168-1175 - [c12]Vikash Kumar, Yuval Tassa, Tom Erez, Emanuel Todorov:
Real-time behaviour synthesis for dynamic hand-manipulation. ICRA 2014: 6808-6815 - [c11]Kendall Lowrey, Svetoslav Kolev, Yuval Tassa, Tom Erez, Emanuel Todorov:
Physically-consistent sensor fusion in contact-rich behaviors. IROS 2014: 1656-1662 - 2013
- [c10]Mingyuan Zhong, M. Johnson, Yuval Tassa, Tom Erez, Emo Todorov:
Value function approximation and model predictive control. ADPRL 2013: 100-107 - [c9]Tingfan Wu, Yuval Tassa, Vikash Kumar, Javier R. Movellan, Emanuel Todorov:
STAC: Simultaneous tracking and calibration. Humanoids 2013: 469-476 - 2012
- [c8]Yuval Tassa, Tom Erez, Emanuel Todorov:
Synthesis and stabilization of complex behaviors through online trajectory optimization. IROS 2012: 4906-4913 - [c7]Emanuel Todorov, Tom Erez, Yuval Tassa:
MuJoCo: A physics engine for model-based control. IROS 2012: 5026-5033 - 2011
- [c6]Yuval Tassa, Emanuel Todorov:
High-order local dynamic programming. ADPRL 2011: 70-75 - [c5]Tom Erez, Yuval Tassa, Emanuel Todorov:
Infinite-Horizon Model Predictive Control for Periodic Tasks with Contacts. Robotics: Science and Systems 2011 - 2010
- [c4]Evangelos A. Theodorou, Yuval Tassa, Emo Todorov:
Stochastic Differential Dynamic Programming. ACC 2010: 1125-1132 - [c3]Yuval Tassa, Emo Todorov:
Stochastic Complementarity for Local Control of Discontinuous Dynamics. Robotics: Science and Systems 2010
2000 – 2009
- 2009
- [c2]Emanuel Todorov, Yuval Tassa:
Iterative local dynamic programming. ADPRL 2009: 90-95 - 2007
- [j1]Yuval Tassa, Tom Erez:
Least Squares Solutions of the HJB Equation With Neural Network Value-Function Approximators. IEEE Trans. Neural Networks 18(4): 1031-1041 (2007) - [c1]Yuval Tassa, Tom Erez, William D. Smart:
Receding Horizon Differential Dynamic Programming. NIPS 2007: 1465-1472
Coauthor Index
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last updated on 2024-07-27 17:34 CEST by the dblp team
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