4.6k citations · 4.7k across the 5 of their papers we have counts for
3 papers
stat.ML2014★ 18 cited
Deep Directed Generative Autoencoders
Sherjil Ozair, Yoshua Bengio
For discrete data, the likelihood can be rewritten exactly and parametrized into if has enough capacity to put no pro…
stat.ML2014★ 3 cited
On the Equivalence Between Deep NADE and Generative Stochastic Networks
Li Yao, Sherjil Ozair, Kyunghyun Cho +1
Neural Autoregressive Distribution Estimators (NADEs) have recently been shown as successful alternatives for modeling high dimensional multimodal distributions. One issue associat…
stat.ML2014★ 4.6k cited
Generative Adversarial Networks
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza +5
We propose a new framework for estimating generative models via an adversarial process, in which we simultaneously train two models: a generative model G that captures the data dis…