9 citations · 9 across the 2 of their papers we have counts for
3 papers
cs.CL2020
On the Encoder-Decoder Incompatibility in Variational Text Modeling and Beyond
Chen Wu, Prince Zizhuang Wang, William Yang Wang
Variational autoencoders (VAEs) combine latent variables with amortized variational inference, whose optimization usually converges into a trivial local optimum termed posterior co…
cs.CL2019
Neural Gaussian Copula for Variational Autoencoder
Prince Zizhuang Wang, William Yang Wang
Variational language models seek to estimate the posterior of latent variables with an approximated variational posterior. The model often assumes the variational posterior to be f…
cs.CL2019★ 9 cited
Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling
Prince Zizhuang Wang, William Yang Wang
Recurrent Variational Autoencoder has been widely used for language modeling and text generation tasks. These models often face a difficult optimization problem, also known as the…