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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations
Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, et al.
(2018)
Open Access | Times Cited: 644

Showing 1-25 of 644 citing articles:

Learning Synergies Between Pushing and Grasping with Self-Supervised Deep Reinforcement Learning
Andy Zeng, Shuran Song, Stefan Welker, et al.
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2018)
Open Access | Times Cited: 524
Electronic skins and machine learning for intelligent soft robots
Benjamin Shih, Dylan Shah, Jinxing Li, et al.
Science Robotics (2020) Vol. 5, Iss. 41
Open Access | Times Cited: 513
Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey
Wenshuai Zhao, Jorge Peña Queralta, Tomi Westerlund
2021 IEEE Symposium Series on Computational Intelligence (SSCI) (2020), pp. 737-744
Open Access | Times Cited: 487
Continuous control for robot based on deep reinforcement learning
Shansi Zhang
(2019)
Open Access | Times Cited: 482
Conservative Q-Learning for Offline Reinforcement Learning
Aviral Kumar, Aurick Zhou, George Tucker, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 454
Cobot programming for collaborative industrial tasks: An overview
Shirine El Zaatari, Mohamed Marei, Weidong Li, et al.
Robotics and Autonomous Systems (2019) Vol. 116, pp. 162-180
Open Access | Times Cited: 361
Residual Reinforcement Learning for Robot Control
Tobias Johannink, Shikhar Bahl, Ashvin Nair, et al.
2022 International Conference on Robotics and Automation (ICRA) (2019), pp. 6023-6029
Open Access | Times Cited: 335
D4RL: Datasets for Deep Data-Driven Reinforcement Learning
Justin Fu, Aviral Kumar, Ofir Nachum, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 318
A Review of Tactile Information: Perception and Action Through Touch
Qiang Li, Oliver Kroemer, Zhe Su, et al.
IEEE Transactions on Robotics (2020) Vol. 36, Iss. 6, pp. 1619-1634
Open Access | Times Cited: 204
Reinforcement and Imitation Learning for Diverse Visuomotor Skills
Yuke Zhu, Ziyu Wang, Josh Merel, et al.
(2018)
Open Access | Times Cited: 199
End-To-End Robotic Reinforcement Learning without Reward Engineering
Avi Singh, Larry Yang, Chelsea Finn, et al.
(2019)
Open Access | Times Cited: 198
A Review of Physics Simulators for Robotic Applications
Jack Collins, Shelvin Chand, Anthony Vanderkop, et al.
IEEE Access (2021) Vol. 9, pp. 51416-51431
Open Access | Times Cited: 170
Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
Xue Bin Peng, Aviral Kumar, Grace Zhang, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 154
Deep Reinforcement Learning for Industrial Insertion Tasks with Visual Inputs and Natural Rewards
Gerrit Schoettler, Ashvin Nair, Jianlan Luo, et al.
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2020), pp. 5548-5555
Open Access | Times Cited: 152
Learning to Manipulate Deformable Objects without Demonstrations
Yilin Wu, Wilson Yan, Thanard Kurutach, et al.
(2020)
Open Access | Times Cited: 150
Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost
Henry Zhu, Abhishek Gupta, Aravind Rajeswaran, et al.
2022 International Conference on Robotics and Automation (ICRA) (2019), pp. 3651-3657
Open Access | Times Cited: 148
A Survey on Offline Reinforcement Learning: Taxonomy, Review, and Open Problems
Rafael Figueiredo Prudencio, Marcos R. O. A. Máximo, Esther Luna Colombini
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 8, pp. 10237-10257
Open Access | Times Cited: 132
Offline Reinforcement Learning with Implicit Q-Learning
Ilya Kostrikov, Ashvin Nair, Sergey Levine
arXiv (Cornell University) (2021)
Open Access | Times Cited: 105
Reinforcement Learning Algorithms and Applications in Healthcare and Robotics: A Comprehensive and Systematic Review
Mokhaled N. A. Al-Hamadani, Mohammed A. Fadhel, Laith Alzubaidi, et al.
Sensors (2024) Vol. 24, Iss. 8, pp. 2461-2461
Open Access | Times Cited: 17
Survey of imitation learning for robotic manipulation
Bin Fang, Shidong Jia, Di Guo, et al.
International Journal of Intelligent Robotics and Applications (2019) Vol. 3, Iss. 4, pp. 362-369
Closed Access | Times Cited: 118
Reinforcement learning for robot research: A comprehensive review and open issues
Tengteng Zhang, Hongwei Mo
International Journal of Advanced Robotic Systems (2021) Vol. 18, Iss. 3
Open Access | Times Cited: 87
PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learning
Guillaume Sartoretti, Justin Kerr, Yunfei Shi, et al.
IEEE Robotics and Automation Letters (2019) Vol. 4, Iss. 3, pp. 2378-2385
Open Access | Times Cited: 86
Review of Deep Reinforcement Learning-Based Object Grasping: Techniques, Open Challenges, and Recommendations
Marwan Qaid Mohammed, Lee Chung Kwek, Shing Chyi Chua
IEEE Access (2020) Vol. 8, pp. 178450-178481
Open Access | Times Cited: 81
Projection-Based Constrained Policy Optimization
Tsung-Yen Yang, Justinian Rosca, Karthik Narasimhan, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 77
Emergent Tool Use From Multi-Agent Autocurricula
Bowen Baker, Ingmar Kanitscheider, Todor Markov, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 77
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