NeurIPS 2019poster66 citations
Inverting Deep Generative models, One layer at a time
Qi Lei, Ajil Jalal, Inderjit S Dhillon, Alexandros G Dimakis
Abstract
We study the problem of inverting a deep generative model with ReLU activations. Inversion corresponds to finding a latent code vector that explains observed measurements as much as possible. In most prior works this is performed by attempting to solve a non-convex optimization problem involving the generator. In this paper we obtain several novel theoretical results for the inversion problem.
BibTeX
@inproceedings{NEURIPS2019_24389bfe,
author = {Lei, Qi and Jalal, Ajil and Dhillon, Inderjit S and Dimakis, Alexandros G},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Inverting Deep Generative models, One layer at a time},
url = {https://proceedings.neurips.cc/paper_files/paper/2019/file/24389bfe4fe2eba8bf9aa9203a44cdad-Paper.pdf},
volume = {32},
year = {2019}
}