Research on Graph Neural Networks Based on Optimization Problems
In order to explore the essential relationship between various models of graph neural networks and better apply graph neural networks to solve practical problems,starting from three graph neural networks based on spatial domain,under a unified optimization framework,three specific optimization problems are obtained from different convolutional kernels,and the expression of information propagation mechanism is obtained by solving these problems.The results indicate that the propagation mechanisms of each model correspond to the solutions of optimization problems under specific graph regularization terms,and the difference lies in the design of convolution kernels.This study provides ideas for designing new variants of graph neural networks.
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