Quantum Convolutional Neural Networks with Interaction Layers for Classification of Classical Data

Jishnu Mahmud, Raisa Mashtura, Shaikh Anowarul Fattah, Mohammad Saquib
7/20/2023
quant-phcs.LG

Official code: chacconed/Quantum-Convolutional-Neural-Networks-with-Interaction-Layers-for-Classification-of-Classical-Data (5 stars, Apache-2.0, last commit 2024-04-27).

Abstract

Quantum Machine Learning (QML) has come into the limelight due to the exceptional computational abilities of quantum computers. With the promises of near error-free quantum computers in the not-so-distant future, it is important that the effect of multi-qubit interactions on quantum neural networks is studied extensively. This paper introduces a Quantum Convolutional Network with novel Interaction layers exploiting three-qubit interactions, while studying the network's expressibility and entangling capability, for classifying both image and one-dimensional data. The proposed approach is tested on three publicly available datasets namely MNIST, Fashion MNIST, and Iris datasets, flexible in performing binary and multiclass classifications, and is found to supersede the performance of existing state-of-the-art methods.

View on arXivView PDF

Code Implementations(1)

chacconed/Quantum-Convolutional-Neural-Networks-with-Interaction-Layers-for-Classification-of-Classical-DataOfficial
Apache-2.0

Exploring the performance of a network for three-qubit gates in quantum convolutional neural networks

51Jupyter NotebookJul 20, 20232 years agoApache-2.0

Similar Papers

Quantum machine learning for image classification

89% match1 repo332023

Selective Feature Re-Encoded Quantum Convolutional Neural Network with Joint Optimization for Image Classification

89% match2025

Hybrid Quantum-Classical Learning for Multiclass Image Classification

88% match2025

Impact of Data Augmentation on QCNNs

88% match2023

Efficient Quantum Convolutional Neural Networks for Image Classification: Overcoming Hardware Constraints

88% match2025

Bridging Classical and Quantum Machine Learning: Knowledge Transfer From Classical to Quantum Neural Networks Using Knowledge Distillation

87% match2023

Cite this paper

@article{mahmud2023quantum,
  title  = {Quantum Convolutional Neural Networks with Interaction Layers for Classification of Classical Data},
  author = {Jishnu Mahmud and Raisa Mashtura and Shaikh Anowarul Fattah and Mohammad Saquib},
  year   = {2023},
  eprint = {2307.11792},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2307.11792v3}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2307.11792.svg)](https://codeofpaper.com/paper/2307.11792)

Discussion