Sylvester Normalizing Flows for Variational Inference

@inproceedings{Berg2018SylvesterNF,
  title={Sylvester Normalizing Flows for Variational Inference},
  author={Rianne van den Berg and Leonard Hasenclever and Jakub M. Tomczak and Max Welling},
  booktitle={UAI},
  year={2018}
}
Variational inference relies on flexible approximate posterior distributions. Normalizing flows provide a general recipe to construct flexible variational posteriors. We introduce Sylvester normalizing flows, which can be seen as a generalization of planar flows. Sylvester normalizing flows remove the well-known single-unit bottleneck from planar flows, making a single transformation much more flexible. We compare the performance of Sylvester normalizing flows against planar flows and inverse… CONTINUE READING
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