# black box variational inference (wip)

04 February 2017

notes on (Ranganath, Gerrish, & Blei, 2014).

## summary

understanding: 7/10

a key paper for modern variational inference. the elbo is maximized using a score function gradient estimator. the main problem is high variance of gradient estimators. two variance reduction techniques are presented:

• rao-blackwellization
• control variates

i don’t understand control variates very well.

## references

1. Ranganath, R., Gerrish, S., & Blei, D. (2014). Black Box Variational Inference. In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics (pp. 814–822).
@inproceedings{ranganath2014black,
title = {Black Box Variational Inference},
author = {Ranganath, Rajesh and Gerrish, Sean and Blei, David},
booktitle = {Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics},
pages = {814--822},
year = {2014}
}


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