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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:

AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search
Linnan Wang, Yiyang Zhao, Yuu Jinnai, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 61

Showing 1-25 of 61 citing articles:

A Survey on Neural Architecture Search
Martin Wistuba, Ambrish Rawat, Tejaswini Pedapati
arXiv (Cornell University) (2019)
Open Access | Times Cited: 204
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search
Colin White, Willie Neiswanger, Yash Savani
Proceedings of the AAAI Conference on Artificial Intelligence (2021) Vol. 35, Iss. 12, pp. 10293-10301
Open Access | Times Cited: 180
Evaluating the Search Phase of Neural Architecture Search
Kaicheng Yu, Christian Sciuto, Martin Jaggi, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 169
Compute Trends Across Three Eras of Machine Learning
Jaime Sevilla, Lennart Heim, Anson Ho, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2022), pp. 1-8
Open Access | Times Cited: 168
Evaluating The Search Phase of Neural Architecture Search
Kaicheng Yu, Christian Sciuto, Martin Jaggi, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 162
Improving One-Shot NAS by Suppressing the Posterior Fading
Xiang Li, Lin Chen, Chuming Li, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020)
Open Access | Times Cited: 73
Weight-Sharing Neural Architecture Search: A Battle to Shrink the Optimization Gap
Lingxi Xie, Xin Chen, Kaifeng Bi, et al.
ACM Computing Surveys (2021) Vol. 54, Iss. 9, pp. 1-37
Open Access | Times Cited: 69
Neural predictor based quantum architecture search
Shi‐Xin Zhang, Chang‐Yu Hsieh, Shengyu Zhang, et al.
Machine Learning Science and Technology (2021) Vol. 2, Iss. 4, pp. 045027-045027
Open Access | Times Cited: 59
Rethinking neural architecture representation for predictors: Topological encoding in pixel space
Caiyang Yu, Jian Wang, Yifan Wang, et al.
Information Fusion (2025), pp. 102925-102925
Closed Access
Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS
Shi Han, Renjie Pi, Hang Xu, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 49
Automated Design of Deep Neural Networks
El‐Ghazali Talbi
ACM Computing Surveys (2021) Vol. 54, Iss. 2, pp. 1-37
Closed Access | Times Cited: 32
Sample-Efficient Neural Architecture Search by Learning Action Space
Linnan Wang, Saining Xie, Teng Li, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 39
ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero
Yuandong Tian, Jerry Ma, Qucheng Gong, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 36
AutoFeature: Searching for Feature Interactions and Their Architectures for Click-through Rate Prediction
Farhan Khawar, Xu Hang, Ruiming Tang, et al.
(2020)
Closed Access | Times Cited: 35
vPipe: A Virtualized Acceleration System for Achieving Efficient and Scalable Pipeline Parallel DNN Training
Shixiong Zhao, Fanxin Li, Xusheng Chen, et al.
IEEE Transactions on Parallel and Distributed Systems (2021) Vol. 33, Iss. 3, pp. 489-506
Open Access | Times Cited: 30
Advances in neural architecture search
Xin Wang, Wenwu Zhu
National Science Review (2024) Vol. 11, Iss. 8
Open Access | Times Cited: 3
Few-shot Neural Architecture Search
Yiyang Zhao, Linnan Wang, Yuandong Tian, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 25
Part-X: A Family of Stochastic Algorithms for Search-Based Test Generation With Probabilistic Guarantees
Giulia Pedrielli, Tanmay Khandait, Yumeng Cao, et al.
IEEE Transactions on Automation Science and Engineering (2023) Vol. 21, Iss. 3, pp. 4504-4525
Open Access | Times Cited: 8
Weight-Sharing Neural Architecture Search: A Battle to Shrink the Optimization Gap
Lingxi Xie, Xin Chen, Kaifeng Bi, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 23
A Generic Graph-based Neural Architecture Encoding Scheme for Predictor-based NAS
Xuefei Ning, Yin Zheng, Tianchen Zhao, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 20
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search
Linnan Wang, Rodrigo Fonseca, Yuandong Tian
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 18
Compute Trends Across Three Eras of Machine Learning
Jaime Sevilla, Lennart Heim, Anson Ho, et al.
arXiv (Cornell University) (2022)
Open Access | Times Cited: 11
Graph Masked Autoencoder Enhanced Predictor for Neural Architecture Search
Kun Jing, Jungang Xu, Pengfei Li
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (2022), pp. 3114-3120
Open Access | Times Cited: 10
Toward Evolutionary Multitask Convolutional Neural Architecture Search
Xun Zhou, Zhenkun Wang, Liang Feng, et al.
IEEE Transactions on Evolutionary Computation (2023) Vol. 28, Iss. 3, pp. 682-695
Closed Access | Times Cited: 5
Neural Predictor based Quantum Architecture Search
Shi‐Xin Zhang, Chang‐Yu Hsieh, Shengyu Zhang, et al.
arXiv (Cornell University) (2021)
Closed Access | Times Cited: 13
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