Graphs are ubiquitous, and they can model unique characteristics complex relations of real-life systems. Although using machine learning (ML) on graphs is promising, their raw representation not suitable for ML algorithms. Graph embedding represents each node a graph as d-dimensional vector which more tasks. However, the process expensive, CPU-based tools do scale to real-world graphs. In this ...

Abstract Graph convolutional network (GCN) has made remarkable progress in learning good representations from graph-structured data. The layer-wise propagation rule of conventional GCN is designed such a way that the feature aggregation at each node depends on features one-hop neighbouring nodes. Adding an attention layer over can allow to provide different importance within various neighbours....

In recent years graph embedding has emerged as a promising solution for enabling the expressive, convenient, powerful but computational expensive graph based representations to benefit from mature, less expensive and efficient state of the art machine learning models of statistical pattern recognition. In this paper we present a comparison of two implicit and three explicit state of the art gra...

A topological book embedding of a graph is an embedding in a book that carries the vertices in the spine of the book and the edges in the pages so that edges are allowed to cross the spine. Recently, the author has shown that for an arbitrary graph G with n vertices there exists a d + 1page book embedding of G in which each edge crosses the spine logd n times. This paper improves the result for...

The purpose of embedding (or mapping) is to minimize the communication overhead of parallel algorithms. It appears unlikely that an efficient exact technique of embedding a general guest graph in a general host graph with a minimum-dilation will ever be found. The Research in this area is concentrating on discovering efficient heuristic that find solution in most cases. This article is a survey...

We study the VLSI-related problem of embedding graphs in books. A book embedding of a graph G =(V ,E) consists of two parts, namely, (1) an ordering of V along the spine of the book, and (2) an assignment of each eE E to a page of the book, so that edges assigned to the same page do not intersect. In devising an-embedding, one seeks to minimi;ze the number of pages used. This paper addresses a ...