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:

Subtleties in the trainability of quantum machine learning models
Supanut Thanasilp, Samson Wang, Nhat A. Nghiem, et al.
Quantum Machine Intelligence (2023) Vol. 5, Iss. 1
Open Access | Times Cited: 42

Showing 1-25 of 42 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: 296
Diagnosing Barren Plateaus with Tools from Quantum Optimal Control
Martín Larocca, Piotr Czarnik, Kunal Sharma, et al.
Quantum (2022) Vol. 6, pp. 824-824
Open Access | Times Cited: 145
Equivalence of quantum barren plateaus to cost concentration and narrow gorges
Andrew Arrasmith, Zoë Holmes, M. Cerezo, et al.
Quantum Science and Technology (2022) Vol. 7, Iss. 4, pp. 045015-045015
Open Access | Times Cited: 104
Quantum Computing for High-Energy Physics: State of the Art and Challenges
Alberto Di Meglio, Karl Jansen, Ivano Tavernelli, et al.
PRX Quantum (2024) Vol. 5, Iss. 3
Open Access | Times Cited: 50
Theoretical guarantees for permutation-equivariant quantum neural networks
Louis Schatzki, Martín Larocca, Quynh T. Nguyen, et al.
npj Quantum Information (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 40
A Lie algebraic theory of barren plateaus for deep parameterized quantum circuits
Michael Ragone, Bojko Bakalov, Frédéric Sauvage, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 32
On the practical usefulness of the Hardware Efficient Ansatz
Lorenzo Leone, Salvatore F. E. Oliviero, Łukasz Cincio, et al.
Quantum (2024) Vol. 8, pp. 1395-1395
Open Access | Times Cited: 21
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: 20
Variational Quantum Simulation: A Case Study for Understanding Warm Starts
Ricard Puig, Marc Drudis, Supanut Thanasilp, et al.
PRX Quantum (2025) Vol. 6, Iss. 1
Open Access | Times Cited: 2
Barren plateaus swamped with traps
Nikita A. Nemkov, Evgeniy O. Kiktenko, Aleksey K. Fedorov
Physical review. A/Physical review, A (2025) Vol. 111, Iss. 1
Closed Access | Times Cited: 2
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
Trainability barriers and opportunities in quantum generative modeling
Manuel S. Rudolph, Sacha Lerch, Supanut Thanasilp, et al.
npj Quantum Information (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 13
Investigating and mitigating barren plateaus in variational quantum circuits: a survey
Jack R. Cunningham, Jun Zhuang
Quantum Information Processing (2025) Vol. 24, Iss. 2
Open Access | Times Cited: 1
Quantum Computing for High-Energy Physics: State of the Art and Challenges. Summary of the QC4HEP Working Group
Alberto Di Meglio, Karl Jansen, Ivano Tavernelli, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 22
Tight and Efficient Gradient Bounds for Parameterized Quantum Circuits
Alistair Letcher, Stefan Woerner, Christa Zoufal
Quantum (2024) Vol. 8, pp. 1484-1484
Open Access | Times Cited: 7
A semi-agnostic ansatz with variable structure for quantum machine learning
M. Bilkis, M. Cerezo, Guillaume Verdon, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 36
Theory for Equivariant Quantum Neural Networks
Kate Nguyen, Louis Schatzki, Paolo Braccia, et al.
arXiv (Cornell University) (2022)
Open Access | Times Cited: 24
Problem-Dependent Power of Quantum Neural Networks on Multiclass Classification
Yuxuan Du, Yibo Yang, Dacheng Tao, et al.
Physical Review Letters (2023) Vol. 131, Iss. 14
Open Access | Times Cited: 16
Design and analysis of quantum machine learning: a survey
Linshu Chen, Tao Li, Yuxiang Chen, et al.
Connection Science (2024) Vol. 36, Iss. 1
Open Access | Times Cited: 5
Symmetry-invariant quantum machine learning force fields
Isabel Nha Minh Le, Oriel Kiss, Julian Schuhmacher, et al.
New Journal of Physics (2025) Vol. 27, Iss. 2, pp. 023015-023015
Open Access
Computing exact moments of local random quantum circuits via tensor networks
Paolo Braccia, Pablo Bermejo, Łukasz Cincio, et al.
Quantum Machine Intelligence (2024) Vol. 6, Iss. 2
Closed Access | Times Cited: 3
Hybrid Tree Tensor Networks for Quantum Simulation
Julian Schuhmacher, Marco Ballarin, Alberto Baiardi, et al.
PRX Quantum (2025) Vol. 6, Iss. 1
Open Access
Unsupervised beyond-standard-model event discovery at the LHC with a novel quantum autoencoder
Callum Duffy, M. H. Hassanshahi, Marcin Jastrzebski, et al.
Quantum Machine Intelligence (2025) Vol. 7, Iss. 1
Open Access
Barren plateaus in variational quantum computing
Martín Larocca, Supanut Thanasilp, Samson Wang, et al.
Nature Reviews Physics (2025)
Closed Access
Review of Optimization Techniques and Barren Plateaus in Training of Quantum Machine Learning Problems
Mandaar B. Pande
Lecture notes in electrical engineering (2025), pp. 3-15
Closed Access
Page 1 - Next Page

Scroll to top