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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:

Encoding-dependent generalization bounds for parametrized quantum circuits
C. Matthias, Elies Gil-Fuster, Johannes Jakob Meyer, et al.
Quantum (2021) Vol. 5, pp. 582-582
Open Access | Times Cited: 77

Showing 1-25 of 77 citing articles:

Challenges and opportunities in quantum machine learning
M. Cerezo, Guillaume Verdon, Hsin-Yuan Huang, et al.
Nature Computational Science (2022) Vol. 2, Iss. 9, pp. 567-576
Closed Access | Times Cited: 288
Generalization in quantum machine learning from few training data
C. Matthias, Hsin-Yuan Huang, M. Cerezo, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 254
Efficient Measure for the Expressivity of Variational Quantum Algorithms
Yuxuan Du, Zhuozhuo Tu, Xiao Yuan, et al.
Physical Review Letters (2022) Vol. 128, Iss. 8
Open Access | Times Cited: 84
Quantum machine learning: from physics to software engineering
Alexey Melnikov, Mohammad Kordzanganeh, A. P. Alodjants, et al.
Advances in Physics X (2023) Vol. 8, Iss. 1
Open Access | Times Cited: 48
Understanding quantum machine learning also requires rethinking generalization
Elies Gil-Fuster, Jens Eisert, Carlos Bravo-Prieto
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 18
Exponential concentration in quantum kernel methods
Supanut Thanasilp, Samson Wang, M. Cerezo, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 18
Dynamical simulation via quantum machine learning with provable generalization
Joe Gibbs, Zoë Holmes, C. Matthias, et al.
Physical Review Research (2024) Vol. 6, Iss. 1
Open Access | Times Cited: 17
On fundamental aspects of quantum extreme learning machines
Weijie Xiong, Giorgio Facelli, Mehrad Sahebi, et al.
Quantum Machine Intelligence (2025) Vol. 7, Iss. 1
Open Access | Times Cited: 3
Experimental quantum adversarial learning with programmable superconducting qubits
Wenhui Ren, Weikang Li, Shibo Xu, et al.
Nature Computational Science (2022) Vol. 2, Iss. 11, pp. 711-717
Open Access | Times Cited: 67
Exponential concentration and untrainability in quantum kernel methods
Supanut Thanasilp, Samson Wang, M. Cerezo, et al.
Research Square (Research Square) (2022)
Open Access | Times Cited: 46
Out-of-distribution generalization for learning quantum dynamics
C. Matthias, Hsin-Yuan Huang, Nicholas Ezzell, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 40
Towards quantum enhanced adversarial robustness in machine learning
Maxwell T. West, S. Tsang, Jia Shun Low, et al.
Nature Machine Intelligence (2023) Vol. 5, Iss. 6, pp. 581-589
Open Access | Times Cited: 32
A survey on the complexity of learning quantum states
Anurag Anshu, Srinivasan Arunachalam
Nature Reviews Physics (2023) Vol. 6, Iss. 1, pp. 59-69
Closed Access | Times Cited: 28
Generalization despite overfitting in quantum machine learning models
Evan Peters, Maria Schuld
Quantum (2023) Vol. 7, pp. 1210-1210
Open Access | Times Cited: 26
Quantum machine learning on near-term quantum devices: Current state of supervised and unsupervised techniques for real-world applications
Yaswitha Gujju, Atsushi Matsuo, Rudy Raymond
Physical Review Applied (2024) Vol. 21, Iss. 6
Open Access | Times Cited: 13
Shadows of quantum machine learning
Sofiène Jerbi, Casper Gyurik, Simon C. Marshall, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 13
Quantum Neural Network Classifiers: A Tutorial
Weikang Li, Zhide Lu, Dong-Ling Deng
SciPost Physics Lecture Notes (2022)
Open Access | Times Cited: 31
Quantum kernel methods for solving regression problems and differential equations
Annie E. Paine, Vincent E. Elfving, Oleksandr Kyriienko
Physical review. A/Physical review, A (2023) Vol. 107, Iss. 3
Open Access | Times Cited: 20
Classical Surrogates for Quantum Learning Models
Franz J. Schreiber, Jens Eisert, Johannes Jakob Meyer
Physical Review Letters (2023) Vol. 131, Iss. 10
Open Access | Times Cited: 18
Exponential data encoding for quantum supervised learning
Seongwook Shin, Yong Siah Teo, Hyunseok Jeong
Physical review. A/Physical review, A (2023) Vol. 107, Iss. 1
Open Access | Times Cited: 17
High Dimensional Quantum Machine Learning With Small Quantum Computers
Simon C. Marshall, Casper Gyurik, Vedran Dunjko
Quantum (2023) Vol. 7, pp. 1078-1078
Open Access | Times Cited: 17
How can quantum computing be applied in clinical trial design and optimization?
Hakan Doğa, Aritra Bose, Mehmet Şahin, et al.
Trends in Pharmacological Sciences (2024) Vol. 45, Iss. 10, pp. 880-891
Open Access | Times Cited: 8
Learning Quantum Processes and Hamiltonians via the Pauli Transfer Matrix
C. Matthias
ACM Transactions on Quantum Computing (2024) Vol. 5, Iss. 2, pp. 1-53
Open Access | Times Cited: 7
Statistical Complexity of Quantum Learning
Leonardo Banchi, Jason L. Pereira, Sharu Theresa Jose, et al.
Advanced Quantum Technologies (2024)
Open Access | Times Cited: 6
Learning Quantum States and Unitaries of Bounded Gate Complexity
Haimeng Zhao, L. Lewis, Ishaan Kannan, et al.
PRX Quantum (2024) Vol. 5, Iss. 4
Open Access | Times Cited: 6
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