Следене
Yuval Tassa
Yuval Tassa
Research Scientist, Google DeepMind
Потвърден имейл адрес: google.com - Начална страница
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Позовавания
Година
Continuous control with deep reinforcement learning
TP Lillicrap, JJ Hunt, A Pritzel, N Heess, T Erez, Y Tassa, D Silver, ...
arXiv preprint arXiv:1509.02971, 2015
95562015
MuJoCo: A physics engine for model-based control
E Todorov, T Erez, Y Tassa
IROS, 2012
32582012
Emergence of locomotion behaviours in rich environments
N Heess, D TB, S Sriram, J Lemmon, J Merel, G Wayne, Y Tassa, T Erez, ...
arXiv preprint arXiv:1707.02286, 2017
7772017
Synthesis and Stabilization of Complex Behaviors through Online Trajectory Optimization
Y Tassa, T Erez, E Todorov
IROS 2012, 2012
7052012
Learning continuous control policies by stochastic value gradients
N Heess, G Wayne, D Silver, T Lillicrap, T Erez, Y Tassa
Advances in neural information processing systems 28, 2015
5092015
Attend, infer, repeat: Fast scene understanding with generative models
SM Eslami, N Heess, T Weber, Y Tassa, D Szepesvari, GE Hinton
Advances in Neural Information Processing Systems 29, 2016
4312016
Control-limited differential dynamic programming
Y Tassa, N Mansard, E Todorov
2014 IEEE International Conference on Robotics and Automation (ICRA), 1168-1175, 2014
3852014
Maximum a posteriori policy optimisation
A Abdolmaleki, JT Springenberg, Y Tassa, R Munos, N Heess, ...
arXiv preprint arXiv:1806.06920, 2018
2942018
Deepmind control suite
Y Tassa, Y Doron, A Muldal, T Erez, Y Li, DL Casas, D Budden, ...
arXiv preprint arXiv:1801.00690, 2018
2792018
Simulation Tools for Model-Based Robotics: Comparison of Bullet, Havok, MuJoCo, ODE and PhysX
T Erez, Y Tassa, E Todorov
ICRA 2015, 0
261*
Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, et al. Deepmind control suite
Y Tassa, Y Doron, A Muldal, T Erez, Y Li
arXiv preprint arXiv:1801.00690 1, 2018
256*2018
Safe exploration in continuous action spaces
G Dalal, K Dvijotham, M Vecerik, T Hester, C Paduraru, Y Tassa
arXiv preprint arXiv:1801.08757, 2018
2362018
Data-efficient deep reinforcement learning for dexterous manipulation
I Popov, N Heess, T Lillicrap, R Hafner, G Barth-Maron, M Vecerik, ...
arXiv preprint arXiv:1704.03073, 2017
2342017
Whole-body model-predictive control applied to the HRP-2 humanoid
J Koenemann, A Del Prete, Y Tassa, E Todorov, O Stasse, M Bennewitz, ...
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015
1882015
Learning and transfer of modulated locomotor controllers
N Heess, G Wayne, Y Tassa, T Lillicrap, M Riedmiller, D Silver
arXiv preprint arXiv:1610.05182, 2016
1822016
Learning human behaviors from motion capture by adversarial imitation
J Merel, Y Tassa, D TB, S Srinivasan, J Lemmon, Z Wang, G Wayne, ...
arXiv preprint arXiv:1707.02201, 2017
1722017
Receding horizon differential dynamic programming
Y Tassa, T Erez, W Smart
Advances in neural information processing systems 20, 2007
1502007
An integrated system for real-time model predictive control of humanoid robots
T Erez, K Lowrey, Y Tassa, V Kumar, S Kolev, E Todorov
2013 13th IEEE-RAS International conference on humanoid robots (Humanoids …, 2013
1482013
Stochastic differential dynamic programming
E Theodorou, Y Tassa, E Todorov
Proceedings of the 2010 American Control Conference, 1125-1132, 2010
1272010
dm_control: Software and tasks for continuous control
S Tunyasuvunakool, A Muldal, Y Doron, S Liu, S Bohez, J Merel, T Erez, ...
Software Impacts 6, 100022, 2020
842020
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