Hierarchical Variational Models

@inproceedings{Ranganath2016HierarchicalVM,
  title={Hierarchical Variational Models},
  author={Rajesh Ranganath and Dustin Tran and David M. Blei},
  booktitle={ICML},
  year={2016}
}
Black box inference allows researchers to easily prototype and evaluate an array of models. Recent advances in variational inference allow such algorithms to scale to high dimensions. However, a central question remains: How to specify an expressive variational distribution which maintains efficient computation? To address this, we develop hierarchical variational models. In a HIERARCHICAL VM, the variational approximation is augmented with a prior on its parameters, such that the latent… CONTINUE READING
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