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Variational Gaussian Process Auto-Encoder for Ordinal Prediction of Facial Action Units
[article]
2016
arXiv
pre-print
We address the task of simultaneous feature fusion and modeling of discrete ordinal outputs. We propose a novel Gaussian process(GP) auto-encoder modeling approach. In particular, we introduce GP encoders to project multiple observed features onto a latent space, while GP decoders are responsible for reconstructing the original features. Inference is performed in a novel variational framework, where the recovered latent representations are further constrained by the ordinal output labels. In
arXiv:1608.04664v2
fatcat:iwfhyyyn35h3posjeogyz7ssw4