mlsanityData to 14 Oct 2026

mathbbZ2× mathbbZ2 Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks

arXiv 2311.18744 ↗First posted 30 Nov 2023quant-ph cs.LG hep-phcited by 4

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Abstract (arXiv)

This paper presents a comprehensive comparative analysis of the performance of Equivariant Quantum Neural Networks (EQNN) and Quantum Neural Networks (QNN), juxtaposed against their classical counterparts: Equivariant Neural Networks (ENN) and Deep Neural Networks (DNN). We evaluate the performance of each network with two toy examples for a binary classification task, focusing on model complexity (measured by the number of parameters) and the size of the training data set. Our results show that the mathbbZ2× mathbbZ2 EQNN and the QNN provide superior performance for smaller parameter sets and modest training data samples.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 19 of its 51 references that are in the map. First posted on arXiv 30 Nov 2023.

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19 of 51 references.

References · 19

  1. 2016Group Equivariant Convolutional Networkscited by 1,165
  2. 2019Gauge Equivariant Convolutional Networks and the Icosahedral CNNcited by 267
  3. 2020Lorentz Group Equivariant Neural Network for Particle Physicscited by 121
  4. 2020Sampling using SU(N) gauge equivariant flowscited by 84
  5. 2021A Living Review of Machine Learning for Particle Physicscited by 78
  6. 2022Exploiting symmetry in variational quantum machine learningcited by 69
  7. 2022Theory for Equivariant Quantum Neural Networkscited by 62
  8. 2020Lattice gauge equivariant convolutional neural networkscited by 45
  9. 2022Equivariant quantum circuits for learning on weighted graphscited by 41
  10. 2022PELICAN: Permutation Equivariant and Lorentz Invariant or Covariant Aggregator Network for Particle Physicscited by 26
  11. 2023EPiC-GAN: Equivariant Point Cloud Generation for Particle Jetscited by 23
  12. 2021Hybrid Quantum-Classical Graph Convolutional Networkcited by 21
7 more
  1. 2021Generalization capabilities of translationally equivariant neural networkscited by 18
  2. 2023A General Framework for Equivariant Neural Networks on Reductive Lie Groupscited by 16
  3. 2022Lorentz group equivariant autoencoderscited by 15
  4. 2022Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learningcited by 10
  5. 2023Approximately Equivariant Quantum Neural Network for p4m Group Symmetries in Imagescited by 10
  6. 2021Quantum Optimisation of Complex Systems with a Quantum Annealercited by 7
  7. 2022Classical versus Quantum: comparing Tensor Network-based Quantum Circuits on LHC datacited by 7

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Cited by year

Citing papers per year: 2024: 3; 2025: 1.

4 papers.

  1. 2025A Primer on Quantum Machine Learningcited by 12
  2. 2024Quantum Vision Transformers for Quark-Gluon Classificationcited by 7
  3. 2024Lorentz-Equivariant Quantum Graph Neural Network for High-Energy Physicscited by 4
  4. 2024Lie-Equivariant Quantum Graph Neural Networkscited by 0