January 2019
Intermediate to advanced
316 pages
8h 16m
English
Content preview from Generative Adversarial Networks Projects
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Feature matching
During the training of GANs, we maximize the objective function of the discriminator network and minimize the objective function of the generator network. This objective function has some serious flaws. For example, it doesn't take into account the statistics of the generated data and the real data.
Feature matching is a technique that was proposed by Tim Salimans, Ian Goodfellow, and others in their paper titled Improved Techniques for Training GANs, to improve the convergence of the GANs by introducing a new objective function. The new objective function for the generator network encourages it to generate data, with statistics, that is similar to the real data.
To apply feature mapping, the network doesn't ask the discriminator ...
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