LCS graph kernel based on Wasserstein distance in longest common subsequence metric space

Author:

Huang Jianming,Fang Zhongxi,Kasai Hiroyuki

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software,Control and Systems Engineering

Reference56 articles.

1. Graph kernels;Vishwanathan;J. Mach. Learn. Res.,2010

2. A survey on graph kernels;Kriege;Appl. Netw. Sci.,2020

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4. Deeper insights into graph convolutional networks for semi-supervised learning;Li,2018

5. Measuring and relieving the over-smoothing problem for graph neural networks from the topological view;Chen,2020

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