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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:

Efficient Discrete Feature Encoding for Variational Quantum Classifier
Hiroshi Yano, Yudai Suzuki, Rudy Raymond, et al.
2022 IEEE International Conference on Quantum Computing and Engineering (QCE) (2020), pp. 11-21
Open Access | Times Cited: 22

Showing 22 citing articles:

Quantum Computing for Finance: State-of-the-Art and Future Prospects
Daniel J. Egger, Claudio Gambella, Jakub Mareček, et al.
IEEE Transactions on Quantum Engineering (2020) Vol. 1, pp. 1-24
Open Access | Times Cited: 278
Solving nonlinear differential equations with differentiable quantum circuits
Oleksandr Kyriienko, Annie E. Paine, Vincent E. Elfving
Physical review. A/Physical review, A (2021) Vol. 103, Iss. 5
Open Access | Times Cited: 128
Mixed Quantum–Classical Method for Fraud Detection With Quantum Feature Selection
Michele Grossi, Noelle Ibrahim, Voica Radescu, et al.
IEEE Transactions on Quantum Engineering (2022) Vol. 3, pp. 1-12
Open Access | Times Cited: 38
Quantum Neural Network Classifiers: A Tutorial
Weikang Li, Zhide Lu, Dong-Ling Deng
SciPost Physics Lecture Notes (2022)
Open Access | Times Cited: 30
Recursive Quantum Relaxation for Combinatorial Optimization Problems
Ruho Kondo, Yuki Sato, Rudy Raymond, et al.
Quantum (2025) Vol. 9, pp. 1594-1594
Open Access
Hybrid Quantum-Classical Neural Networks
Davis Arthur, Prasanna Date
2022 IEEE International Conference on Quantum Computing and Engineering (QCE) (2022), pp. 49-55
Open Access | Times Cited: 19
Quantum Machine Learning for Finance ICCAD Special Session Paper
Marco Pistoia, Syed Farhan Ahmad, Akshay Ajagekar, et al.
2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD) (2021)
Closed Access | Times Cited: 25
Expressivity of Variational Quantum Machine Learning on the Boolean Cube
Dylan Herman, Rudy Raymond, Muyuan Li, et al.
IEEE Transactions on Quantum Engineering (2023) Vol. 4, pp. 1-18
Open Access | Times Cited: 9
A Fully Connected Quantum Convolutional Neural Network for Classifying Ischemic Cardiopathy
Ubaid Ullah, Alain García-Olea Jurado, I Diez Gonzalez, et al.
IEEE Access (2022) Vol. 10, pp. 134592-134605
Open Access | Times Cited: 15
QNet: A Scalable and Noise-Resilient Quantum Neural Network Architecture for Noisy Intermediate-Scale Quantum Computers
Mahabubul Alam, Swaroop Ghosh
Frontiers in Physics (2022) Vol. 9
Open Access | Times Cited: 9
Trainable Discrete Feature Embeddings for Quantum Machine Learning
Napat Thumwanit, Chayaphol Lortaraprasert, Hiroshi Yano, et al.
2022 IEEE International Conference on Quantum Computing and Engineering (QCE) (2021), pp. 479-480
Closed Access | Times Cited: 12
Quantum Machine Learning for Finance
Marco Pistoia, Syed Farhan Ahmad, Akshay Ajagekar, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 9
Quantum federated learning in healthcare: The shift from development to deployment and from models to data
Sabre Kais, Amandeep Singh Bhatia, M. S. Alam
Research Square (Research Square) (2023)
Open Access | Times Cited: 3
A Quantum Neural Network Regression for Modeling Lithium-ion Battery Capacity Degradation
Anh Phuong Ngo, Nhat Le, Hieu T. Nguyen, et al.
(2023), pp. 164-168
Open Access | Times Cited: 3
Invited: Trainable Discrete Feature Embeddings for Quantum Machine Learning
Napat Thumwanit, Chayaphol Lortaraprasert, Rudy Raymond
(2021), pp. 1352-1355
Closed Access | Times Cited: 6
Trainable Discrete Feature Embeddings for Variational Quantum Classifier
Napat Thumwanit, Chayaphol Lortaraprasert, Hiroshi Yano, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 4
Sarcopenia risk prediction and feature selection by using quantum machine learning algorithms
Ubaid Ullah, Danyal Maheshwari, Cristián Castillo-Olea, et al.
Quantum Machine Intelligence (2024) Vol. 6, Iss. 2
Closed Access
New parameterized quantum gates design and efficient gradient solving based on variational quantum classification algorithm
Xiaodong Ding, Fudong Liu, Weilong Wang, et al.
Machine Learning Science and Technology (2024) Vol. 6, Iss. 1, pp. 015004-015004
Open Access
Recent advances for quantum classifiers
Weikang Li, Dong-Ling Deng
arXiv (Cornell University) (2021)
Closed Access | Times Cited: 2
Report on 2206.02806v1
Weikang Li, Zhide Lu, Dong-Ling Deng
arXiv (Cornell University) (2022)
Open Access
Report on 2206.02806v1
Weikang Li, Zhide Lu, Dong-Ling Deng
arXiv (Cornell University) (2022)
Open Access
A Case for Noisy Shallow Gate-based Circuits in Quantum Machine Learning
Patrick Selig, N.P. Murphy, Ashwin Sundareswaran R, et al.
(2021), pp. 24-34
Open Access
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