Hidden Talents of the Variational Autoencoder.

By Bin Dai, Yu Wang, John A. D. Aston, Gang Hua, David Paul Wipf. 2017

37 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Fabio Viola
2. Danilo Jimenez Rezende
3. Yoshua Bengio
4. Sergey Levine
5. Ruslan Salakhutdinov
6. Abhinav Kumar Gupta
7. Diederik P. Kingma
8. Trevor Darrell

Citations in the corpus

• Variational Autoencoders Pursue PCA Directions (by Accident) (2018, neutral): “Several recent works approached this issue [5, 40, 8, 1, 12, 31, 9].”
• Taming VAEs (2018, methodology): “A further extension of the analysis including the incorporation of Lipschitz constraints is also available in Appendix B. Complementary to the analysis from [38] with (semi-)affine assumptions on the VAE’s decoder, we focus on non-linear aspects of high-capacity constrained VAEs.”
• Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse (2019, unknown): “[14] showed that the covariance structure of the variational distribution may smooth out the loss landscape.”