1 code implementation • ACL 2020 • Chen Wu, Prince Zizhuang Wang, William Yang Wang
To this end, we propose Coupled-VAE, which couples a VAE model with a deterministic autoencoder with the same structure and improves the encoder and decoder parameterizations via encoder weight sharing and decoder signal matching.
no code implementations • IJCNLP 2019 • Prince Zizhuang Wang, William Yang Wang
We argue that this would cause a typical training problem called posterior collapse observed in all other variational language models.
1 code implementation • NAACL 2019 • Prince Zizhuang Wang, William Yang Wang
The RNF transforms a latent variable into a space that respects the geometric characteristics of input space, which makes posterior impossible to collapse to the non-informative prior.