Show simple item record Saire Pilco, Darwin Danilo Ramirez Rivera, Gerberth Adin 2021-03-01 2021-02-24
dc.description GLN creates a set of node embeddings H(l) that are later combined to produce an intermediary representation H_int​(l). Then, we use the updated node information with the adjacency information to produce a local embedding of the nodes' information H_local(l)​ that is also the output H(l+1). We also broadcast the information of the local embedding to produce a global embedding H_global​(l). We combine the local and global embeddings to predict the next layer adjacency A(l+1). Additionally, we create three Synthetic Graph Datasets: the 3D-Surface, Community, and Geometric Figures. The source code is available in the public repository and the datasets are available in
dc.description.sponsorship Fundação de Amparo à Pesquisa do Estado de São Paulo
dc.publisher Saire Pilco, Darwin
dc.subject Computer and Information Science
dc.title Graph Learning Network (GLN)
dc.description.sponsorshipId FAPESP: 2017/16597-7

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