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Non-parametric priors for generative adversarial networks
Rajhans Singh
,
Pavan Turaga
,
Suren Jayasuriya
, Ravi Garg
, Martin W. Braun
Arts, Media and Engineering, School of (AME)
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
3
Scopus citations
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Keyphrases
Nonparametric
100%
Generative Adversarial Networks
100%
Latent Space
100%
Space Distribution
50%
Additional Training
25%
Optimization Tool
25%
Network Architecture
25%
Straight Line
25%
Easy-to-implement
25%
Probability Theory
25%
Proposed Formulation
25%
Image Generation
25%
Data Augmentation
25%
Qualitative Properties
25%
Point Distribution
25%
Low Divergence
25%
Space Statistic
25%
Engineering
Image Synthesis
100%
Straight Line
100%
Point Distribution
100%
Additional Training
100%
Qualitative Property
100%
Computer Science
Generative Adversarial Networks
100%
Network Architecture
33%
Formalization
33%
Image Synthesis
33%
Distribution Point
33%
Data Augmentation
33%
Qualitative Property
33%
Mathematics
Parametric
100%
Distribution Space
66%
Probability Theory
33%
Straight Line
33%
Formalization
33%
Arts and Humanities
Generative
100%
Architecture
33%
Capabilities
33%
Formalization
33%