A Neural Autoregressive Topic Model

@inproceedings{Larochelle2012ANA,
  title={A Neural Autoregressive Topic Model},
  author={Hugo Larochelle and Stanislas Lauly},
  booktitle={NIPS},
  year={2012}
}
We describe a new model for learning meaningful representations of text documents from an unlabeled collection of documents. This model is inspired by the recently proposed Replicated Softmax, an undirected graphical model of word counts that was shown to learn a better generative model and more meaningful document representations. Specifically, we take inspiration from the conditional mean-field recursive equations of the Replicated Softmax in order to define a neural network architecture that… CONTINUE READING
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