Cloud-VAE: Variational autoencoder with concepts embedded

•The initial concepts in latent space are described as prior distribution obtained by the proposed cloud model-based clustering algorithm.•Variational lower bound of Cloud-VAE is derived to guide training process and re-construct concepts of latent space, so that the mutual mapping between latent sp...

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Veröffentlicht in:	Pattern recognition Jg. 140; S. 109530
Hauptverfasser:	Liu, Yue, Liu, Zitu, Li, Shuang, Yu, Zhenyao, Guo, Yike, Liu, Qun, Wang, Guoyin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.08.2023
Schlagworte:	Cloud Model Concept embedded Deep Learning Interpretability Disentangled representation Variational autoencoder Variational autoencoder Cloud Model Concept embedded Deep Learning Interpretability Disentangled representation
ISSN:	0031-3203, 1873-5142
Online-Zugang:	Volltext
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