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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:

Quantum phase detection generalization from marginal quantum neural network models
Saverio Monaco, Oriel Kiss, Antonio Mandarino, et al.
Physical review. B./Physical review. B (2023) Vol. 107, Iss. 8
Open Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

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
Quantum error mitigation for Fourier moment computation
Oriel Kiss, Michele Grossi, Alessandro Roggero
Physical review. D/Physical review. D. (2025) Vol. 111, Iss. 3
Open Access | Times Cited: 2
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
Quantum Classical Algorithm for the Study of Phase Transitions in the Hubbard Model via Dynamical Mean-Field Theory
Anshumitra Baul, Herbert Fotso, Hanna Terletska, et al.
Quantum Reports (2025) Vol. 7, Iss. 2, pp. 18-18
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
Model-Independent Learning of Quantum Phases of Matter with Quantum Convolutional Neural Networks
Yu-Jie Liu, Adam Smith, Michael Knap, et al.
Physical Review Letters (2023) Vol. 130, Iss. 22
Open Access | Times Cited: 20
Finite-size criticality in fully connected spin models on superconducting quantum hardware
Michele Grossi, Oriel Kiss, Francesco De Luca, et al.
Physical review. E (2023) Vol. 107, Iss. 2
Open Access | Times Cited: 15
Counterdiabatic optimized driving in quantum phase sensitive models
Francesco Pio Barone, Oriel Kiss, Michele Grossi, et al.
New Journal of Physics (2024) Vol. 26, Iss. 3, pp. 033031-033031
Open Access | Times Cited: 6
Dequantizing quantum machine learning models using tensor networks
Seongwook Shin, Yong Siah Teo, Hyunseok Jeong
Physical Review Research (2024) Vol. 6, Iss. 2
Open Access | Times Cited: 5
Importance sampling for stochastic quantum simulations
Oriel Kiss, Michele Grossi, Alessandro Roggero
Quantum (2023) Vol. 7, pp. 977-977
Open Access | Times Cited: 12
Nuclear Physics in the Era of Quantum Computing and Quantum Machine Learning
J. E. García-Ramos, Álvaro Sáiz, J. M. Arias, et al.
Advanced Quantum Technologies (2024)
Open Access | Times Cited: 4
Approximately Equivariant Quantum Neural Network for p4m Group Symmetries in Images
Su Yeon Chang, Michele Grossi, Bertrand Le Saux, et al.
2022 IEEE International Conference on Quantum Computing and Engineering (QCE) (2023), pp. 229-235
Open Access | Times Cited: 10
Effective detection of quantum discord by using convolutional neural networks
Narjes Taghadomi, Awadhesh Mani, A. Fahim, et al.
Quantum Machine Intelligence (2025) Vol. 7, Iss. 1
Closed Access
Early Fault-Tolerant Quantum Algorithms in Practice: Application to Ground-State Energy Estimation
Oriel Kiss, Utkarsh Azad, Borja Requena, et al.
Quantum (2025) Vol. 9, pp. 1682-1682
Open Access
Hybrid ground-state quantum algorithms based on neural Schrödinger forging
Paulin de Schoulepnikoff, Oriel Kiss, S. Vallecorsa, et al.
Physical Review Research (2024) Vol. 6, Iss. 2
Open Access | Times Cited: 3
Splitting and parallelizing of quantum convolutional neural networks for learning translationally symmetric data
Koki Chinzei, Quoc Hoan Tran, Kazunori Maruyama, et al.
Physical Review Research (2024) Vol. 6, Iss. 2
Open Access | Times Cited: 3
Detecting quantum phase transitions in a frustrated spin chain via transfer learning of a quantum classifier algorithm
André J. Ferreira–Martins, Leandro Silva, Alberto Palhares, et al.
Physical review. A/Physical review, A (2024) Vol. 109, Iss. 5
Open Access | Times Cited: 2
Quantum-Classical-Quantum Workflow in Quantum-HPC Middleware with GPU Acceleration
Kuan‐Cheng Chen, Xiaoren Li, Xiaotian Xu, et al.
(2024), pp. 304-311
Closed Access | Times Cited: 2
Quantum data learning for quantum simulations in high-energy physics
Lento Nagano, Alexander Miessen, Tamiya Onodera, et al.
Physical Review Research (2023) Vol. 5, Iss. 4
Open Access | Times Cited: 6
Experimentally realizable continuous-variable quantum neural networks
Shikha Bangar, Leanto Sunny, Kübra Yeter‐Aydeniz, et al.
Physical review. A/Physical review, A (2023) Vol. 108, Iss. 4
Open Access | Times Cited: 4
A Tutorial on the Use of Physics-Informed Neural Networks to Compute the Spectrum of Quantum Systems
Lorenzo Brevi, Antonio Mandarino, Enrico Prati
Technologies (2024) Vol. 12, Iss. 10, pp. 174-174
Open Access | Times Cited: 1
Permutation-equivariant quantum convolutional neural networks
Sreetama Das, Filippo Caruso
Quantum Science and Technology (2024) Vol. 10, Iss. 1, pp. 015030-015030
Open Access | Times Cited: 1
Hybrid Ground-State Quantum Algorithms based on Neural Schrödinger Forging
Paulin de Schoulepnikoff, Oriel Kiss, Sofia Vallecorsa, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 1
Channel attention for quantum convolutional neural networks
Gekko Budiutama, Shunsuke Daimon, Hirofumi Nishi, et al.
Physical review. A/Physical review, A (2024) Vol. 110, Iss. 1
Open Access
Enforcing exact permutation and rotational symmetries in the application of quantum neural networks on point cloud datasets
Zhelun Li, Lento Nagano, K. Terashi
Physical Review Research (2024) Vol. 6, Iss. 4
Open Access
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