Latent Normalizing Flows for Discrete Sequences

Zachary M. Ziegler
Zachary M. Ziegler

arXiv: Machine Learning, 2019.

Cited by: 25|Bibtex|Views111
EI
Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

Normalizing flows have been shown to be a powerful class of generative models for continuous random variables, giving both strong performance and the potential for non-autoregressive generation. These benefits are also desired when modeling discrete random variables such as text, but directly applying normalizing flows to discrete sequenc...More

Code:

Data:

Full Text
Your rating :
0

 

Tags
Comments