Variational auto-encoder based Bayesian Poisson tensor factorization for sparse and imbalanced count data

Jin, Yuan, Liu, Ming, Li, Yungfeng, Xu, Ruohua, Du, Lan, Gao, Longxiang and Xiang, Yong 2020, Variational auto-encoder based Bayesian Poisson tensor factorization for sparse and imbalanced count data, Data mining and knowledge discovery, pp. 1-28, doi: 10.1007/s10618-020-00723-7.

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Title Variational auto-encoder based Bayesian Poisson tensor factorization for sparse and imbalanced count data
Author(s) Jin, Yuan
Liu, MingORCID iD for Liu, Ming orcid.org/0000-0002-2160-6111
Li, Yungfeng
Xu, Ruohua
Du, Lan
Gao, LongxiangORCID iD for Gao, Longxiang orcid.org/0000-0002-3026-7537
Xiang, YongORCID iD for Xiang, Yong orcid.org/0000-0003-3545-7863
Journal name Data mining and knowledge discovery
Start page 1
End page 28
Total pages 28
Publisher Springer
Place of publication New York, N.Y.
Publication date 2020-12-10
ISSN 1384-5810
1573-756X
Keyword(s) Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Information Systems
Computer Science
Non-negative tensor factorization
Variational auto-encoders
Neural networks
Latent variable modelling
Count data
Notes Article in Press
Language eng
DOI 10.1007/s10618-020-00723-7
Indigenous content off
Field of Research 0801 Artificial Intelligence and Image Processing
0804 Data Format
0806 Information Systems
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30146328

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