Using Skill Rating as Fitness on the Evolution of GANs

EvoApplications, pp. 562-577, 2020.

Cited by: 0|Bibtex|Views2|DOI:https://doi.org/10.1007/978-3-030-43722-0_36
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Other Links: dblp.uni-trier.de|arxiv.org|academic.microsoft.com

Abstract:

Generative Adversarial Networks (GANs) are an adversarial model that achieved impressive results on generative tasks. In spite of the relevant results, GANs present some challenges regarding stability, making the training usually a hit-and-miss process. To overcome these challenges, several improvements were proposed to better handle th...More

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