Skip to main navigation
Skip to search
Skip to main content
EdUHK Research Repository Home
About the Repository
Home
Researchers
Research Units
Projects
Research Outputs
Prizes and Awards
KT Activities
Search by expertise, name or affiliation
Learning latent superstructures in variational autoencoders for deep multidimensional clustering
Xiaopeng LI
, Zhourong CHEN
, Kin Man POON
, Nevin L. ZHANG
Department of Mathematics and Information Technology (MIT)
Research output
:
Contribution to conference
›
Poster
28
Citations (Scopus)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Learning latent superstructures in variational autoencoders for deep multidimensional clustering'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Mathematics
Clustering
100%
Gaussian Mixture Model
100%
Dimensional Data
100%
Tree Structure
100%
Deep Learning
100%
Keyphrases
Multidimensional Clustering
100%
Variational Autoencoder
100%
Latent Variables
75%
Latent Feature
50%
Copyright
25%
Multiple Partitions
25%
Gaussian Mixture Model
25%
Deep Learning Methods
25%
Tree Structure
25%
High-dimensional Data
25%
Discrete Latent Variables
25%
Psychology
Mixture Model
100%
Gaussian Distribution
100%
Clustering
100%
Computer Science
Autoencoder
100%
Multiple Partition
25%
Gaussian Mixture Model
25%
High Dimensional Data
25%
Deep Learning
25%
Chemical Engineering
Deep Learning
100%