Epitomic Variational Graph Autoencoder

Variational autoencoder (VAE) is a widely used generative model for learning latent representations. Burda et al. [3] in their seminal paper showed that learning capacity of VAE is limited by over-pruning. It is a phenomenon where a significant number of latent variables fail to capture any informat...

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Bibliographic Details

Published in:	2020 25th International Conference on Pattern Recognition (ICPR) pp. 7203 - 7210
Main Authors:	Khan, Rayyan Ahmad, Anwaar, Muhammad Umer, Kleinsteuber, Martin
Format:	Conference Proceeding
Language:	English
Published:	IEEE 10.01.2021
Subjects:	Benchmark testing EVGAE Graph auto encoder Graph neural networks Over-pruning Pattern recognition Task analysis VAE Variational graph autoencoder
Online Access:	Get full text
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