Analyzing noise in autoencoders and deep networks

6 Jun 2014Ben PooleJascha Sohl-DicksteinSurya Ganguli

Autoencoders have emerged as a useful framework for unsupervised learning of internal representations, and a wide variety of apparently conceptually disparate regularization techniques have been proposed to generate useful features. Here we extend existing denoising autoencoders to additionally inject noise before the nonlinearity, and at the hidden unit activations... (read more)

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