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Jingwei Zhang
Jingwei Zhang
DeepMind
Bestätigte E-Mail-Adresse bei google.com
Titel
Zitiert von
Zitiert von
Jahr
Deep reinforcement learning with successor features for navigation across similar environments
J Zhang, JT Springenberg, J Boedecker, W Burgard
2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017
3092017
Socially compliant navigation through raw depth inputs with generative adversarial imitation learning
L Tai, J Zhang, M Liu, W Burgard
2018 IEEE international conference on robotics and automation (ICRA), 1111-1117, 2018
2232018
Neural slam: Learning to explore with external memory
J Zhang, L Tai, J Boedecker, W Burgard, M Liu
arXiv preprint arXiv:1706.09520, 2017
1752017
Vr-goggles for robots: Real-to-sim domain adaptation for visual control
J Zhang, L Tai, P Yun, Y Xiong, M Liu, J Boedecker, W Burgard
IEEE Robotics and Automation Letters 4 (2), 1148-1155, 2019
1372019
Curiosity-driven exploration for mapless navigation with deep reinforcement learning
O Zhelo, J Zhang, L Tai, M Liu, W Burgard
arXiv preprint arXiv:1804.00456, 2018
1272018
A survey of deep network solutions for learning control in robotics: From reinforcement to imitation
L Tai, J Zhang, M Liu, J Boedecker, W Burgard
arXiv preprint arXiv:1612.07139, 2016
972016
Genie: Generative interactive environments
J Bruce, MD Dennis, A Edwards, J Parker-Holder, Y Shi, E Hughes, M Lai, ...
Forty-first International Conference on Machine Learning, 2024
882024
Deep reinforcement learning with successor features for navigation across similar environments. In 2017 IEEE
J Zhang, JT Springenberg, J Boedecker, W Burgard
RSJ International Conference on Intelligent Robots and Systems (IROS), 2371-2378, 0
45
Attend2Pack: Bin packing through deep reinforcement learning with attention
J Zhang, B Zi, X Ge
arXiv preprint arXiv:2107.04333, 2021
282021
A generalist dynamics model for control
I Schubert, J Zhang, J Bruce, S Bechtle, E Parisotto, M Riedmiller, ...
arXiv preprint arXiv:2305.10912, 2023
262023
Scheduled intrinsic drive: A hierarchical take on intrinsically motivated exploration
J Zhang, N Wetzel, N Dorka, J Boedecker, W Burgard
arXiv preprint arXiv:1903.07400, 2019
262019
Efficiency and equity are both essential: A generalized traffic signal controller with deep reinforcement learning
S Yan, J Zhang, D Büscher, W Burgard
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020
142020
Perspectives on Deep Multimodel Robot Learning
W Burgard, A Valada, N Radwan, T Naseer, J Zhang, J Vertens, O Mees, ...
11*
Offline actor-critic reinforcement learning scales to large models
JT Springenberg, A Abdolmaleki, J Zhang, O Groth, M Bloesch, T Lampe, ...
arXiv preprint arXiv:2402.05546, 2024
62024
Leveraging jumpy models for planning and fast learning in robotic domains
J Zhang, JT Springenberg, A Byravan, L Hasenclever, A Abdolmaleki, ...
arXiv preprint arXiv:2302.12617, 2023
52023
Supplement file of VR-Goggles for robots: Real-to-sim domain adaptation for visual control
J Zhang, L Tai, PYYXM Liu, JBW Burgard
Training 853 (840), 715, 2018
42018
Mastering stacking of diverse shapes with large-scale iterative reinforcement learning on real robots
T Lampe, A Abdolmaleki, S Bechtle, SH Huang, JT Springenberg, ...
2024 IEEE International Conference on Robotics and Automation (ICRA), 7772-7779, 2024
32024
Equivariant Data Augmentation for Generalization in Offline Reinforcement Learning
C Pinneri, S Bechtle, M Wulfmeier, A Byravan, J Zhang, WF Whitney, ...
arXiv preprint arXiv:2309.07578, 2023
32023
pytorch-dnc
J Zhang
https://github.com/jingweiz/pytorch-dnc, 2017
2017
pytorch-rl
J Zhang, L Tai
https://github.com/jingweiz/pytorch-rl, 2017
2017
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