Generative Adversarial Networks and Image Synthesis
Open access
Abstract
Abstract
In this paper, we explore the inclusion of latent random variables into the hidden state of a recurrent neural network (RNN) by combining the elements of the variational autoencoder. We argue that through the use of high-level latent random variables, the variational RNN (VRNN) can model the kind of variability observed in highly structured sequential data such as natural speech. We empirically evaluate the proposed model against other related sequential models on four speech datasets and one handwriting dataset. Our results show the important roles that latent random variables can play in the RNN dynamics.
Direct answer
What can I do from this paper page?
Use this page to scan "A Recurrent Latent Variable Model for Sequential Data" quickly: start with the summary and abstract, then check the authors, source, topics, and related papers. From here, open Scollr to follow Generative Adversarial Networks and Image Synthesis research, save the paper, or map adjacent work.
Research areas
Follow related topics
Citation
BibTeX
@article{Dinh2026Recurrent,
title = {A Recurrent Latent Variable Model for Sequential Data},
author = {Laurent Dinh and Kratarth Goel and Jun‐Young Chung and Kyle Kastner and Aaron Courville and Yoshua Bengio},
journal = {arXiv (Cornell University)},
year = {2026},
doi = {10.5281/zenodo.19983308},
url = {https://arxiv.org/pdf/1506.02216.pdf}
}FAQ
Using this paper in a discovery workflow
How do I find related work for this paper?
Use the related papers and topic links on this page as starting points. In Scollr, you can also open the paper and build a literature map around its references, citing papers, and related work.
How can I keep up with new Generative Adversarial Networks and Image Synthesis research papers?
Follow Generative Adversarial Networks and Image Synthesis research in Scollr. New papers from the topic flow into a personalized feed, and you can save useful studies to revisit later.
Can I cite this paper from this page?
This page includes a static BibTeX block for A Recurrent Latent Variable Model for Sequential Data. Always verify the DOI, source, and publication details against the publisher record before submitting a manuscript.
Follow this research in Scollr
Follow the topics and authors behind this paper, save useful studies, and build a literature map when you are ready to go deeper.
Get the app