Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Sim-to-Real Transfer of Robotic Control with Dynamics Randomization
Xue Bin Peng, Marcin Andrychowicz, Wojciech Zaremba, et al.
(2018)
Open Access | Times Cited: 1058

Showing 1-25 of 1058 citing articles:

Deep Reinforcement Learning for Autonomous Driving: A Survey
Bangalore Ravi Kiran, Ibrahim Sobh, Victor Talpaert, et al.
IEEE Transactions on Intelligent Transportation Systems (2021) Vol. 23, Iss. 6, pp. 4909-4926
Open Access | Times Cited: 1290
Learning agile and dynamic motor skills for legged robots
Jemin Hwangbo, Joonho Lee, Alexey Dosovitskiy, et al.
Science Robotics (2019) Vol. 4, Iss. 26
Open Access | Times Cited: 1031
Learning quadrupedal locomotion over challenging terrain
Joonho Lee, Jemin Hwangbo, Lorenz Wellhausen, et al.
Science Robotics (2020) Vol. 5, Iss. 47
Open Access | Times Cited: 730
Solving Rubik's Cube with a Robot Hand
OpenAI, Ilge Akkaya, Marcin Andrychowicz, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 655
Sim-to-Real: Learning Agile Locomotion For Quadruped Robots
Jie Tan, Tingnan Zhang, Erwin Coumans, et al.
(2018)
Open Access | Times Cited: 573
Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems
Laura von Rueden, Sebastian Mayer, Katharina Beckh, et al.
IEEE Transactions on Knowledge and Data Engineering (2021), pp. 1-1
Open Access | Times Cited: 556
Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence
Huiying Liang, Brian Tsui, Hao Ni, et al.
Nature Medicine (2019) Vol. 25, Iss. 3, pp. 433-438
Closed Access | Times Cited: 540
Generalizing to Unseen Domains: A Survey on Domain Generalization
Jindong Wang, Cuiling Lan, Chang Liu, et al.
IEEE Transactions on Knowledge and Data Engineering (2022), pp. 1-1
Open Access | Times Cited: 502
Learning ambidextrous robot grasping policies
Jeffrey Mahler, Matthew Matl, Vishal Satish, et al.
Science Robotics (2019) Vol. 4, Iss. 26
Closed Access | Times Cited: 488
Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience
Yevgen Chebotar, Ankur Handa, Viktor Makoviychuk, et al.
2022 International Conference on Robotics and Automation (ICRA) (2019), pp. 8973-8979
Open Access | Times Cited: 409
How to train your robot with deep reinforcement learning: lessons we have learned
Julian Ibarz, Jie Tan, Chelsea Finn, et al.
The International Journal of Robotics Research (2021) Vol. 40, Iss. 4-5, pp. 698-721
Open Access | Times Cited: 380
Sim-To-Real via Sim-To-Sim: Data-Efficient Robotic Grasping via Randomized-To-Canonical Adaptation Networks
Stephen James, Paul Wohlhart, Mrinal Kalakrishnan, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019), pp. 12619-12629
Closed Access | Times Cited: 367
Challenges of real-world reinforcement learning: definitions, benchmarks and analysis
Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, et al.
Machine Learning (2021) Vol. 110, Iss. 9, pp. 2419-2468
Open Access | Times Cited: 314
Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks
Michelle A. Lee, Yuke Zhu, Krishnan Srinivasan, et al.
2022 International Conference on Robotics and Automation (ICRA) (2019), pp. 8943-8950
Open Access | Times Cited: 308
Learning Agile Robotic Locomotion Skills by Imitating Animals
Xue Bin Peng, Erwin Coumans, Tingnan Zhang, et al.
(2020)
Open Access | Times Cited: 277
Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient
Shihui Li, Yi Wu, Xinyue Cui, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2019) Vol. 33, Iss. 01, pp. 4213-4220
Open Access | Times Cited: 226
Recent advances on industrial data-driven energy savings: Digital twins and infrastructures
Sin Yong Teng, Michal Touš, Wei Dong Leong, et al.
Renewable and Sustainable Energy Reviews (2020) Vol. 135, pp. 110208-110208
Closed Access | Times Cited: 226
A Survey on Learning-Based Robotic Grasping
Kilian Kleeberger, Richard Bormann, Werner Kraus, et al.
Current Robotics Reports (2020) Vol. 1, Iss. 4, pp. 239-249
Open Access | Times Cited: 209
Challenges of Real-World Reinforcement Learning
Gabriel Dulac-Arnold, Daniel J. Mankowitz, Todd Hester
arXiv (Cornell University) (2019)
Closed Access | Times Cited: 205
Deep reinforcement learning: a survey
Haonan Wang, Ning Liu, Yiyun Zhang, et al.
Frontiers of Information Technology & Electronic Engineering (2020) Vol. 21, Iss. 12, pp. 1726-1744
Closed Access | Times Cited: 202
First return, then explore
Adrien Ecoffet, Joost Huizinga, Joel Lehman, et al.
Nature (2021) Vol. 590, Iss. 7847, pp. 580-586
Closed Access | Times Cited: 201
Reinforcement and Imitation Learning for Diverse Visuomotor Skills
Yuke Zhu, Ziyu Wang, Josh Merel, et al.
(2018)
Open Access | Times Cited: 199
Review of Deep Reinforcement Learning for Robot Manipulation
Van‐Dinh Nguyen, Hung Manh La
2019 Third IEEE International Conference on Robotic Computing (IRC) (2019), pp. 590-595
Closed Access | Times Cited: 195
RLBench: The Robot Learning Benchmark & Learning Environment
Stephen James, Zicong Ma, David Rovick Arrojo, et al.
IEEE Robotics and Automation Letters (2020) Vol. 5, Iss. 2, pp. 3019-3026
Closed Access | Times Cited: 193
Towards Out-Of-Distribution Generalization: A Survey
Zheyan Shen, Jiashuo Liu, Yue He, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 183
Page 1 - Next Page

Scroll to top