Stochastic Backpropagation and Approximate Inference in Deep Generative Models — mentioned by themann9

Sat, 05 Sep 2015 02:08:05 GMT

Not me dude but I like underdogs and outsiders. What u saying sounds right: symmetries, like the ones computed in section 3.8 are used as constraints a.k.a. "quantum numbers" describing the states in the latent layer. That is vintage quantum mechanics. The part is theoretical and not in the theano code by looks of it, so harder to comment on... The quantum analogy also brings along the laplacian form of the conditional density in section 1.5, so there u go. On your comment, which "literature on the topic" is clear? Have u read the original VAE paper http://arxiv.org/pdf/1401.4082.pdf. 95% of…

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Stochastic Backpropagation and Approximate Inference in Deep Generative Models · HackerPapers discussions

Stochastic Backpropagation and Approximate Inference in Deep Generative Models — mentioned by themann9