Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning

We propose a symmetric graph convolutional autoencoder which produces a low-dimensional latent representation from a graph. In contrast to the existing graph autoencoders with asymmetric decoder parts, the proposed autoencoder has a newly designed decoder which builds a completely symmetric autoenco...

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Bibliographic Details

Published in:	Proceedings / IEEE International Conference on Computer Vision pp. 6518 - 6527
Main Authors:	Park, Jiwoong, Lee, Minsik, Chang, Hyung Jin, Lee, Kyuewang, Choi, Jin Young
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.10.2019
Subjects:	Chebyshev approximation Convolution Decoding Image reconstruction Laplace equations Smoothing methods Task analysis
ISSN:	2380-7504
Online Access:	Get full text
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