Semi-Implicit Stochastic Recurrent Neural Networks
ICASSP, pp. 3342-3346, 2019.
Stochastic recurrent neural networks with latent random variables of complex dependency structures have shown to be more successful in modeling sequential data than deterministic deep models. However, the majority of existing methods have limited expressive power due to the Gaussian assumption of latent variables. In this paper, we advo...More
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