The content discusses the development of hybrid quantum-inspired neural networks based on Resnet and Densenet architectures. These models show promising results in pattern recognition tasks, outperforming traditional models in resistance to parameter attacks and gradient explosion problems. The paper highlights the importance of completeness theory in evaluating the performance of these novel neural networks.
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by Andi Chen,Hu... at arxiv.org 03-12-2024
https://arxiv.org/pdf/2403.05754.pdfDeeper Inquiries