3 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.LG2015★ 2 cited
GSNs : Generative Stochastic Networks
Guillaume Alain, Yoshua Bengio, Li Yao +4
We introduce a novel training principle for probabilistic models that is an alternative to maximum likelihood. The proposed Generative Stochastic Networks (GSN) framework is based…
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…