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Variational Gaussian Process Auto-Encoder for Ordinal Prediction of Facial Action Units
[chapter]
2017
Lecture Notes in Computer Science
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
doi:10.1007/978-3-319-54184-6_10
fatcat:4ujqaspn4feejni45iaym7j73m