3 papers
quant-ph2025
Knowledge Distillation for Variational Quantum Convolutional Neural Networks on Heterogeneous Data
Kai Yu, Binbin Cai, Song Lin
Distributed quantum machine learning faces significant challenges due to heterogeneous client data and variations in local model structures, which hinder global model aggregation.…
quant-ph2025
Quantum Graph Convolutional Networks Based on Spectral Methods
Zi Ye, Kai Yu, Song Lin
Graph Convolutional Networks (GCNs) are specialized neural networks for feature extraction from graph-structured data. In contrast to traditional convolutional networks, GCNs offer…
quant-ph2024
Quantum Convolutional Neural Network with Flexible Stride
Kai Yu, Song Lin, Bin-Bin Cai
Convolutional neural network is a crucial tool for machine learning, especially in the field of computer vision. Its unique structure and characteristics provide significant advant…