Thanard Kurutach
Title
Cited by
Cited by
Year
Model-ensemble trust-region policy optimization
T Kurutach, I Clavera, Y Duan, A Tamar, P Abbeel
arXiv preprint arXiv:1802.10592, 2018
1622018
Learning plannable representations with causal infogan
T Kurutach, A Tamar, G Yang, SJ Russell, P Abbeel
Advances in Neural Information Processing Systems, 8733-8744, 2018
772018
Learning robotic manipulation through visual planning and acting
A Wang, T Kurutach, K Liu, P Abbeel, A Tamar
arXiv preprint arXiv:1905.04411, 2019
262019
Learning to manipulate deformable objects without demonstrations
Y Wu, W Yan, T Kurutach, L Pinto, P Abbeel
arXiv preprint arXiv:1910.13439, 2019
202019
Deep variational semi-supervised novelty detection
T Daniel, T Kurutach, A Tamar
arXiv preprint arXiv:1911.04971, 2019
82019
Hallucinative Topological Memory for Zero-Shot Visual Planning
K Liu, T Kurutach, C Tung, P Abbeel, A Tamar
arXiv preprint arXiv:2002.12336, 2020
42020
Object-based world modeling in semi-static environments with dependent Dirichlet-process mixtures
LLS Wong, T Kurutach, LP Kaelbling, T Lozano-Pérez
arXiv preprint arXiv:1512.00573, 2015
42015
Sparse Graphical Memory for Robust Planning
M Laskin, S Emmons, A Jain, T Kurutach, P Abbeel, D Pathak
arXiv preprint arXiv:2003.06417, 2020
32020
Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning
Y Seo, K Lee, I Clavera Gilaberte, T Kurutach, J Shin, P Abbeel
Advances in Neural Information Processing Systems 33, 2020
2020
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Articles 1–9