Recurrent Variational Autoencoders for Learning Nonlinear Generative Models in the Presence of Outliers.
IEEE Journal of Selected Topics in Signal Processing(2018)
摘要
This paper explores two useful modifications of the recent variational autoencoder (VAE), a popular deep generative modeling framework that dresses traditional autoencoders with probabilistic attire. The first involves a specially-tailored form of conditioning that allows us to simplify the VAE decoder structure while simultaneously introducing robustness to outliers. In a related vein, a second, ...
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关键词
Principal component analysis,Computational modeling,Bayes methods,Deep learning,Upper bound,Probabilistic logic
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