Multiview Deep Graph Infomax to Achieve Unsupervised Graph Embedding.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2022.3163721
Abstract: Unsupervised graph embedding aims to extract highly discriminative node representations that facilitate the subsequent analysis. Converging evidence shows that a multiview graph provides a more comprehensive relationship between nodes than a single-view graph to capture… read more here.
Keywords: node representations; multiview deep; graph; unsupervised graph ... See more keywords
Unsupervised Graph Embedding via Adaptive Graph Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2022.3202158
Abstract: Graph autoencoders (GAEs) are powerful tools in representation learning for graph embedding. However, the performance of GAEs is very dependent on the quality of the graph structure, i.e., of the adjacency matrix. In other words,… read more here.
Keywords: embedding via; unsupervised graph; graph; graph embedding ... See more keywords
Hierarchical and Unsupervised Graph Representation Learning with Loukas's Coarsening
Sign Up to like & getrecommendations! Published in 2020 at "Algorithms"
DOI: 10.3390/a13090206
Abstract: We propose a novel algorithm for unsupervised graph representation learning with attributed graphs. It combines three advantages addressing some current limitations of the literature: (i) The model is inductive: it can embed new graphs without… read more here.
Keywords: unsupervised graph; hierarchical unsupervised; graph representation; representation learning ... See more keywords