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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:

Selective Experience Replay for Lifelong Learning
David Isele, Akansel Cosgun
Proceedings of the AAAI Conference on Artificial Intelligence (2018) Vol. 32, Iss. 1
Open Access | Times Cited: 294

Showing 1-25 of 294 citing articles:

A continual learning survey: Defying forgetting in classification tasks
Matthias Delange, Rahaf Aljundi, Marc Masana, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2021), pp. 1-1
Open Access | Times Cited: 1145
A survey and critique of multiagent deep reinforcement learning
Pablo Hernández-Leal, Bilal Kartal, Matthew E. Taylor
Autonomous Agents and Multi-Agent Systems (2019) Vol. 33, Iss. 6, pp. 750-797
Closed Access | Times Cited: 494
Experience Replay for Continual Learning
David Rolnick, Arun Ahuja, Jonathan Schwarz, et al.
arXiv (Cornell University) (2018)
Open Access | Times Cited: 344
Navigating Occluded Intersections with Autonomous Vehicles Using Deep Reinforcement Learning
David Isele, Reza Rahimi, Akansel Cosgun, et al.
(2018), pp. 2034-2039
Closed Access | Times Cited: 337
Off-Policy Deep Reinforcement Learning without Exploration
Scott Fujimoto, David Meger, Doina Precup
arXiv (Cornell University) (2018)
Open Access | Times Cited: 225
Motion Planning Networks: Bridging the Gap Between Learning-Based and Classical Motion Planners
Ahmed H. Qureshi, Yinglong Miao, Anthony Simeonov, et al.
IEEE Transactions on Robotics (2020) Vol. 37, Iss. 1, pp. 48-66
Open Access | Times Cited: 176
Using Hindsight to Anchor Past Knowledge in Continual Learning
Arslan Chaudhry, Albert Gordo, Puneet K. Dokania, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2021) Vol. 35, Iss. 8, pp. 6993-7001
Open Access | Times Cited: 145
Towards Continual Reinforcement Learning: A Review and Perspectives
Khimya Khetarpal, Matthew Riemer, Irina Rish, et al.
Journal of Artificial Intelligence Research (2022) Vol. 75, pp. 1401-1476
Open Access | Times Cited: 113
Deep reinforcement learning in recommender systems: A survey and new perspectives
Xiaocong Chen, Lina Yao, Julian McAuley, et al.
Knowledge-Based Systems (2023) Vol. 264, pp. 110335-110335
Open Access | Times Cited: 84
A wholistic view of continual learning with deep neural networks: Forgotten lessons and the bridge to active and open world learning
Martin Mundt, Yongwon Hong, Iuliia Pliushch, et al.
Neural Networks (2023) Vol. 160, pp. 306-336
Open Access | Times Cited: 83
Deep Class-Incremental Learning: A Survey
Da-Wei Zhou, Qiwei Wang, Zhihong Qi, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 57
Class-Incremental Learning: A Survey
Da-Wei Zhou, Qiwei Wang, Zhihong Qi, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2024) Vol. 46, Iss. 12, pp. 9851-9873
Open Access | Times Cited: 31
What and How: Generalized Lifelong Spectral Clustering via Dual Memory
Gan Sun, Yang Cong, Jiahua Dong, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2021), pp. 1-1
Closed Access | Times Cited: 88
Replay in Deep Learning: Current Approaches and Missing Biological Elements
Tyler L. Hayes, Giri P. Krishnan, Maxim Bazhenov, et al.
Neural Computation (2021), pp. 1-44
Open Access | Times Cited: 85
Pseudo-rehearsal: Achieving deep reinforcement learning without catastrophic forgetting
Craig Atkinson, Brendan McCane, Lech Szymanski, et al.
Neurocomputing (2020) Vol. 428, pp. 291-307
Open Access | Times Cited: 70
Ensemble reinforcement learning: A survey
Yanjie Song, Ponnuthurai Nagaratnam Suganthan, Witold Pedrycz, et al.
Applied Soft Computing (2023) Vol. 149, pp. 110975-110975
Open Access | Times Cited: 25
Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models
Zangwei Zheng, Mingyuan Ma, Kai Wang, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2023), pp. 19068-19079
Open Access | Times Cited: 24
A collective AI via lifelong learning and sharing at the edge
Andrea Soltoggio, Eseoghene Ben-Iwhiwhu, Vladimir Braverman, et al.
Nature Machine Intelligence (2024) Vol. 6, Iss. 3, pp. 251-264
Open Access | Times Cited: 12
Continual learning for cross-modal image-text retrieval based on domain-selective attention
Rui Yang, Shuang Wang, Yu Gu, et al.
Pattern Recognition (2024) Vol. 149, pp. 110273-110273
Closed Access | Times Cited: 9
Imbalanced Continual Learning with Partitioning Reservoir Sampling
Chris Dongjoo Kim, Jinseo Jeong, Gunhee Kim
Lecture notes in computer science (2020), pp. 411-428
Open Access | Times Cited: 64
Risk-Aware High-level Decisions for Automated Driving at Occluded Intersections with Reinforcement Learning
Danial Kamran, Carlos Fernandez Lopez, Martin Lauer, et al.
2022 IEEE Intelligent Vehicles Symposium (IV) (2020)
Open Access | Times Cited: 59
Progressive learning: A deep learning framework for continual learning
Haytham M. Fayek, Lawrence Cavedon, Hong Ren Wu
Neural Networks (2020) Vol. 128, pp. 345-357
Closed Access | Times Cited: 51
Unsupervised Model Adaptation for Continual Semantic Segmentation
Serban Stan, Mohammad Rostami
Proceedings of the AAAI Conference on Artificial Intelligence (2021) Vol. 35, Iss. 3, pp. 2593-2601
Open Access | Times Cited: 46
An Efficient Domain-Incremental Learning Approach to Drive in All Weather Conditions
M. Jehanzeb Mirza, Marc Masana, Horst Possegger, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (2022), pp. 3000-3010
Open Access | Times Cited: 32
Learning to Continuously Optimize Wireless Resource in a Dynamic Environment: A Bilevel Optimization Perspective
Haoran Sun, Wenqiang Pu, Xiao Fu, et al.
IEEE Transactions on Signal Processing (2022) Vol. 70, pp. 1900-1917
Open Access | Times Cited: 28
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