Locally-connected transformations for deep GMMs

By Aäron van den Oord, Joni Dambre. 2015

17 citations recorded by the source corpus.

Subfields: Generative Models

How researchers see this paper

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

In Generative Models

1. Aäron van den Oord
2. Stefano Ermon
3. Diederik P. Kingma
4. Lucas Theis
5. Laurent Dinh
6. Matthias Bethge
7. Jascha Narain Sohl-Dickstein
8. Yoshua Bengio

Citations in the corpus

• A note on the evaluation of generative models (2015, background): “For instance, already for the 32 by 32 images found in the CIFAR-10 dataset the difference between log-likelihoods of different models can be in the thousands, while log(100) is only about 4.61 nats (van den Oord & Dambre, 2015).”
• A RAD approach to deep mixture models (2019, background): “While this is not necessary, we will exploit this structure as highlighted later in the main text and in Figure 4. et al., 2017), some of which can be expressed as a deep mixture model (Tang et al., 2012; Van den Oord & Schrauwen, 2014; van den Oord & Dambre, 2015).”