mlsanityData to 7 Oct 2026

Quantum Neural Network Classifiers: A Tutorial

arXiv 2206.02806 ↗First posted 6 Jun 2022quant-ph cond-mat.dis-nn cs.AIcited by 13

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Abstract (arXiv)

Machine learning has achieved dramatic success over the past decade, with applications ranging from face recognition to natural language processing. Meanwhile, rapid progress has been made in the field of quantum computation including developing both powerful quantum algorithms and advanced quantum devices. The interplay between machine learning and quantum physics holds the intriguing potential for bringing practical applications to the modern society. Here, we focus on quantum neural networks in the form of parameterized quantum circuits. We will mainly discuss different structures and encoding strategies of quantum neural networks for supervised learning tasks, and benchmark their performance utilizing Yao.jl, a quantum simulation package written in Julia Language. The codes are efficient, aiming to provide convenience for beginners in scientific works such as developing powerful variational quantum learning models and assisting the corresponding experimental demonstrations.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 38 of its 113 references that are in the map. First posted on arXiv 6 Jun 2022.

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38 of 113 references.

References · 38

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 3; 2024: 4; 2025: 2; 2026: 1.

13 papers.

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  1. 2022Recent Advances for Quantum Neural Networks in Generative Learningcited by 39
  2. 2023Towards quantum enhanced adversarial robustness in machine learningcited by 26
  3. 2022Reservoir Computing via Quantum Recurrent Neural Networkscited by 14
  4. 2022QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learningcited by 7
  5. 2023Expressibility-induced Concentration of Quantum Neural Tangent Kernelscited by 7
  6. 2024Quantum-Classical Separations in Shallow-Circuit-Based Learning with and without Noisescited by 3
  7. 2023Universal adversarial perturbations for multiple classification tasks with quantum classifierscited by 1
  8. 2025PALQO: Physics-informed Model for Accelerating Large-scale Quantum Optimizationcited by 1
  9. 2024Multi-Scale Feature Fusion Quantum Depthwise Convolutional Neural Networks for Text Classificationcited by 0
  10. 2024Quantum-data-driven dynamical transition in quantum learningcited by 0
  11. 2024Assessing Superposition-Targeted Coverage Criteria for Quantum Neural Networkscited by 0
  12. 2025Quantum automated learning with provable and explainable trainabilitycited by 0
1 more
  1. 2026QuanForge: A Mutation Testing Framework for Quantum Neural Networkscited by 0