Analysis of Nonautonomous Adversarial Systems
Machine Learning
2018-03-15 v1 Machine Learning
Abstract
Generative adversarial networks are used to generate images but still their convergence properties are not well understood. There have been a few studies who intended to investigate the stability properties of GANs as a dynamical system. This short writing can be seen in that direction. Among the proposed methods for stabilizing training of GANs, {\ss}-GAN was the first who proposed a complete annealing strategy to change high-level conditions of the GAN objective. In this note, we show by a simple example how annealing strategy works in GANs. The theoretical analysis is supported by simple simulations.
Cite
@article{arxiv.1803.05045,
title = {Analysis of Nonautonomous Adversarial Systems},
author = {Arash Mehrjou},
journal= {arXiv preprint arXiv:1803.05045},
year = {2018}
}
Comments
5 pages