AutoQML: Automatic generation and training of robust quantum-inspired classifiers by using evolutionary algorithms on grayscale images-Reference-Cited by-同舟云学术

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AutoQML: Automatic generation and training of robust quantum-inspired classifiers by using evolutionary algorithms on grayscale images

Published:2024-06 Issue: Volume:244 Page:122984
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Altares-López Sergio^ORCID,García-Ripoll Juan José^ORCID,Ribeiro Angela^ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference84 articles.

1. The power of quantum neural networks;Abbas;Nature Computational Science,2021

2. PDE: a Pareto-frontier differential evolution approach for multi-objective optimization problems;Abbass,2001

3. Automatic design of quantum feature maps;Altares-López;Quantum Science and Technology,2021

4. Quantum-inspired computational imaging;Altmann;Science,2018

5. Natural evolutionary strategies for variational quantum computation;Anand;Machine Learning: Science and Technology,2021

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Gradient-based optimization for quantum architecture search;Neural Networks;2024-11

2. Quantum Architecture Search with Neural Predictor Based on Graph Measures;Advanced Quantum Technologies;2024-08-12

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