223 citations · 556 across the 23 of their papers we have counts for
4 papers · 1 filter
Prescribed Generative Adversarial Networks
Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei +1
Generative adversarial networks (GANs) are a powerful approach to unsupervised learning. They have achieved state-of-the-art performance in the image domain. However, GANs are limi…
Topic Modeling in Embedding Spaces
Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei
Topic modeling analyzes documents to learn meaningful patterns of words. However, existing topic models fail to learn interpretable topics when working with large and heavy-tailed…
The Dynamic Embedded Topic Model
Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei
Topic modeling analyzes documents to learn meaningful patterns of words. For documents collected in sequence, dynamic topic models capture how these patterns vary over time. We dev…
Reweighted Expectation Maximization
Adji B. Dieng, John Paisley
Training deep generative models with maximum likelihood remains a challenge. The typical workaround is to use variational inference (VI) and maximize a lower bound to the log margi…