Sequential Neural Models with Stochastic Layers

NeurIPS 2016 Marco FraccaroSøren Kaae SønderbyUlrich PaquetOle Winther

How can we efficiently propagate uncertainty in a latent state representation with recurrent neural networks? This paper introduces stochastic recurrent neural networks which glue a deterministic recurrent neural network and a state space model together to form a stochastic and sequential neural generative model... (read more)

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