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arXiv · 1210.8353

Temporal Autoencoding Restricted Boltzmann Machine

Chris Häusler·Alex Susemihl
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Abstract

Much work has been done refining and characterizing the receptive fields learned by deep learning algorithms. A lot of this work has focused on the development of Gabor-like filters learned when enforcing sparsity constraints on a natural image dataset. Little work however has investigated how these filters might expand to the temporal domain, namely through training on natural movies. Here we investigate exactly this problem in established temporal deep learning algorithms as well as a new learning paradigm suggested here, the Temporal Autoencoding Restricted Boltzmann Machine (TARBM).

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Chris Häusler, Alex Susemihl. 2012-10-31. Temporal Autoencoding Restricted Boltzmann Machine. https://arxiv.org/abs/1210.8353

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