Dec 13, 2022 · In this paper, we propose Complementary Random Walk (CRW) to solve this problem and embed the nodes in a network to obtain more robust low- ...
In this paper, we propose Complementary Random Walk (CRW). Compared with previous random walk based approaches, CRW provides more varied walking paths which ...
Dive into the research topics of 'Complementary Random Walk: A New Perspective on Graph Embedding'. Together they form a unique fingerprint. Sort by; Weight ...
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Existing research on random walk-based graph embedding methods is very rich. In order to summarize and classify the status quo of the more mature classical ...
Jun 12, 2019 · Graph embedding learning that aims to automatically learn low-dimensional node representations, has drawn increasing attention in recent years.
The paper discusses a new method for sampling from a graph, called "repelling random walks". This approach is shown to improve upon standard random walk methods ...
We conduct a comparative analysis of several random walk strategies, including the true self-avoiding random walk and the traditional random walk. We also ...
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Apr 25, 2022 · In this paper, we propose a principled new way for unbiased graph embedding ... pling process of random walk on graphs by giving each group of.
Sep 13, 2022 · Yes, random walks are used as an approximation of diffusion processes on graphs - for the simple reason that diffusion is a continuous view of ...
In this paper, we propose a different approach for obtaining graph representations. We capitalize on well- established concepts from graph kernels and we employ ...