Corpus ID: 216078090

Auto-Encoding Variational Bayes

@article{Kingma2014AutoEncodingVB,
  title={Auto-Encoding Variational Bayes},
  author={Diederik P. Kingma and M. Welling},
  journal={CoRR},
  year={2014},
  volume={abs/1312.6114}
}
Abstract: How can we perform efficient inference and learning in directed probabilistic models, in the presence of continuous latent variables with intractable posterior distributions, and large datasets. [...] Key Method First, we show that a reparameterization of the variational lower bound yields a lower bound estimator that can be straightforwardly optimized using standard stochastic gradient methods. Second, we show that for i.i.d.Expand
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