2.2k citations · 3.1k across the 17 of their papers we have counts for
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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…
cs.LG2014★ 8 cited
Multimodal Transitions for Generative Stochastic Networks
Sherjil Ozair, Li Yao, Yoshua Bengio
Generative Stochastic Networks (GSNs) have been recently introduced as an alternative to traditional probabilistic modeling: instead of parametrizing the data distribution directly…