Neural Autoregressive Distribution Estimation

7 May 2016Benigno UriaMarc-Alexandre CôtéKarol GregorIain MurrayHugo Larochelle

We present Neural Autoregressive Distribution Estimation (NADE) models, which are neural network architectures applied to the problem of unsupervised distribution and density estimation. They leverage the probability product rule and a weight sharing scheme inspired from restricted Boltzmann machines, to yield an estimator that is both tractable and has good generalization performance... (read more)

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