mlsanityData to 7 Oct 2026

A Leap among Quantum Computing and Quantum Neural Networks: A Survey

arXiv 2107.03313 ↗First posted 6 Jul 2021quant-ph cs.ET stat.MLcited by 8

Not on the map. Why?

Abstract (arXiv)

In recent years, Quantum Computing witnessed massive improvements in terms of available resources and algorithms development. The ability to harness quantum phenomena to solve computational problems is a long-standing dream that has drawn the scientific community's interest since the late 80s. In such a context, we propose our contribution. First, we introduce basic concepts related to quantum computations, and then we explain the core functionalities of technologies that implement the Gate Model and Adiabatic Quantum Computing paradigms. Finally, we gather, compare and analyze the current state-of-the-art concerning Quantum Perceptrons and Quantum Neural Networks implementations.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 35 of its 199 references that are in the map. First posted on arXiv 6 Jul 2021.

Builds on

35 of 199 references.

References · 35

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2018Representation Learning with Contrastive Predictive Codingcited by 7,662
  4. 2019Momentum Contrast for Unsupervised Visual Representation Learningcited by 7,482
  5. 2016An overview of gradient descent optimization algorithmscited by 1,021
  6. 2020Variational Quantum Algorithmscited by 687
  7. 2018Supervised learning with quantum enhanced feature spacescited by 654
  8. 2018Barren plateaus in quantum neural network training landscapescited by 624
  9. 2019Parameterized quantum circuits as machine learning modelscited by 330
  10. 2020The effect of data encoding on the expressive power of variational quantum machine learning modelscited by 328
  11. 2019Ab-Initio Solution of the Many-Electron Schr"odinger Equation with Deep Neural Networkscited by 195
  12. 2020Noise-Induced Barren Plateaus in Variational Quantum Algorithmscited by 192
23 more
  1. 2021Connecting ansatz expressibility to gradient magnitudes and barren plateauscited by 180
  2. 2019Efficient Learning for Deep Quantum Neural Networkscited by 160
  3. 2020Absence of Barren Plateaus in Quantum Convolutional Neural Networkscited by 124
  4. 2019Transfer learning in hybrid classical-quantum neural networkscited by 113
  5. 2017Quantum machine learning: a classical perspectivecited by 95
  6. 2020Layerwise learning for quantum neural networkscited by 87
  7. 2018Continuous-variable quantum neural networkscited by 74
  8. 2019Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctionscited by 73
  9. 2019Quantum Graph Neural Networkscited by 66
  10. 2020Trainability of Dissipative Perceptron-Based Quantum Neural Networkscited by 56
  11. 2018q-means: A quantum algorithm for unsupervised machine learningcited by 55
  12. 2019Learning to learn with quantum neural networks via classical neural networkscited by 55
  13. 2017Quantum Neuron: an elementary building block for machine learning on quantum computerscited by 34
  14. 2019Input Redundancy for Parameterized Quantum Circuitscited by 33
  15. 2016Quantum Perceptron Modelscited by 27
  16. 2017Equivalence of restricted Boltzmann machines and tensor network statescited by 26
  17. 2021Quantum Self-Supervised Learningcited by 20
  18. 2014Simulating a perceptron on a quantum computercited by 16
  19. 2018Universal discriminative quantum neural networkscited by 16
  20. 2020Quantum computing for energy systems optimization: Challenges and opportunitiescited by 15
  21. 2020Qibo: a framework for quantum simulation with hardware accelerationcited by 10
  22. 2021The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learningcited by 9
  23. 2020A Derivative-free Method for Quantum Perceptron Training in Multi-layered Neural Networkscited by 3

Built on by

Cited by year

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

8 papers.

  1. 2022Recent Advances for Quantum Neural Networks in Generative Learningcited by 39
  2. 2023A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Aheadcited by 29
  3. 2025Quantum-enhanced Computer Vision: Going Beyond Classical Algorithmscited by 5
  4. 2022Quark: A Gradient-Free Quantum Learning Framework for Classification Taskscited by 4
  5. 2023Quantum Shadow Gradient Descent for Variational Quantum Algorithmscited by 1
  6. 2024A Quantum-Classical Collaborative Training Architecture Based on Quantum State Fidelitycited by 1
  7. 2025PALQO: Physics-informed Model for Accelerating Large-scale Quantum Optimizationcited by 1
  8. 2023On the explainability of quantum neural networks based on variational quantum circuitscited by 0