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Density Estimation Using Real NVP
This dataset has no description
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Alternating Back-Propagation for Generator Networks
This dataset has no description
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Wasserstein GAN
This dataset has no description
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Flexible Prior Distributions for Deep Generative Models
The dataset induced prior distribution is learned using a secondary GAN named PGAN. This prior is then used to further train the original GAN. -
A Bayesian Non-parametric Approach to Generative Models
Generative models have emerged as a promising technique for producing high-quality im-ages that are indistinguishable from real images. -
SGVAE: Sequential Graph Variational Autoencoder
Generative models of graphs are well-known, but many existing models are limited in scalability and expressivity. We present a novel sequential graphical variational autoencoder... -
Adversarial Feature Learning
Adversarial Feature Learning -
Dynamical Variational Autoencoders: A Comprehensive Review
A comprehensive review of dynamical variational autoencoders -
Auto-encoding variational Bayes
Auto-encoding variational Bayes -
Toy Benchmark Problem
The dataset used in the paper is a toy benchmark problem, where the data is generated by uniform sampling from a compact symmetry group G and other independent factors of...
