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Variational autoencoders learn distributions of high-dimensional data.
Neocognitron: A hierarchical neural network capable of visual pattern recognition
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Stochastic variational inference
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Importance weighted autoencoders
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X. Chen, D. P. Kingma, T. Salimans, Y. Duan, P. Dhariwal, J. Schulman, I. Sutskever, and P. Abbeel · 2016
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Topicrnn: A recurrent neural network with long-range semantic dependency
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Improved variational inference with inverse autoregressive flow
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Adversarial variational bayes: Unifying variational autoencoders and generative adversarial networks
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Neural discrete representation learning
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Improved variational autoencoders for text modeling using dilated convolutions
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Tackling over-pruning in variational autoencoders
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Deep residual learning for image recognition
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Towards deeper understanding of variational autoencoding models
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Fixing a broken elbo
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Semi-amortized variational autoencoders
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Variational autoencoders for collaborative filtering
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