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:

Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection
Sergey Levine, Peter Pástor, Alex Krizhevsky, et al.
The International Journal of Robotics Research (2017) Vol. 37, Iss. 4-5, pp. 421-436
Open Access | Times Cited: 1796

Showing 1-25 of 1796 citing articles:

Deep Reinforcement Learning: A Brief Survey
Kai Arulkumaran, Marc Peter Deisenroth, Miles Brundage, et al.
IEEE Signal Processing Magazine (2017) Vol. 34, Iss. 6, pp. 26-38
Open Access | Times Cited: 3243
On the Opportunities and Risks of Foundation Models
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 1524
Deep Learning in Mobile and Wireless Networking: A Survey
Chaoyun Zhang, Paul Patras, Hamed Haddadi
IEEE Communications Surveys & Tutorials (2019) Vol. 21, Iss. 3, pp. 2224-2287
Open Access | Times Cited: 1497
Learning dexterous in-hand manipulation
OpenAI Marcin Andrychowicz, Bowen Baker, Maciek Chociej, et al.
The International Journal of Robotics Research (2019) Vol. 39, Iss. 1, pp. 3-20
Open Access | Times Cited: 1365
Using DeepLabCut for 3D markerless pose estimation across species and behaviors
Tanmay Nath, Alexander Mathis, An Chi Chen, et al.
Nature Protocols (2019) Vol. 14, Iss. 7, pp. 2152-2176
Open Access | Times Cited: 1128
Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics
Jeffrey Mahler, Jacky Liang, Sherdil Niyaz, et al.
(2017)
Open Access | Times Cited: 1061
Sim-to-Real Transfer of Robotic Control with Dynamics Randomization
Xue Bin Peng, Marcin Andrychowicz, Wojciech Zaremba, et al.
(2018)
Open Access | Times Cited: 1056
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
A brief survey of deep reinforcement learning
Kai Arulkumaran, Marc Peter Deisenroth, Miles Brundage, et al.
arXiv (Cornell University) (2017)
Open Access | Times Cited: 771
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Sergey Levine, Aviral Kumar, George Tucker, et al.
arXiv (Cornell University) (2020)
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
Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community
John Ball, Derek T. Anderson, Chee Seng Chan
Journal of Applied Remote Sensing (2017) Vol. 11, Iss. 04, pp. 1-1
Open Access | Times Cited: 639
Overcoming Exploration in Reinforcement Learning with Demonstrations
Ashvin Nair, Bob McGrew, Marcin Andrychowicz, et al.
(2018), pp. 6292-6299
Open Access | Times Cited: 638
Deep visual foresight for planning robot motion
Chelsea Finn, Sergey Levine
(2017)
Open Access | Times Cited: 634
Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping
Konstantinos Bousmalis, Alex Irpan, Paul Wohlhart, et al.
(2018)
Open Access | Times Cited: 626
Gibson Env: Real-World Perception for Embodied Agents
Fei Xia, Amir Zamir, Zhiyang He, et al.
(2018), pp. 9068-9079
Open Access | Times Cited: 625
Sim-to-Real: Learning Agile Locomotion For Quadruped Robots
Jie Tan, Tingnan Zhang, Erwin Coumans, et al.
(2018)
Open Access | Times Cited: 570
Learning ambidextrous robot grasping policies
Jeffrey Mahler, Matthew Matl, Vishal Satish, et al.
Science Robotics (2019) Vol. 4, Iss. 26
Closed Access | Times Cited: 487
Robotic grasp detection using deep convolutional neural networks
Sulabh Kumra, Christopher Kanan
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2017), pp. 769-776
Open Access | Times Cited: 483
6-DOF GraspNet: Variational Grasp Generation for Object Manipulation
Arsalan Mousavian, Clemens Eppner, Dieter Fox
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2019), pp. 2901-2910
Open Access | Times Cited: 443
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: 408
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
Reinforcement learning for building controls: The opportunities and challenges
Zhe Wang, Tianzhen Hong
Applied Energy (2020) Vol. 269, pp. 115036-115036
Open Access | Times Cited: 379
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: 366
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
Page 1 - Next Page

Scroll to top