Generative Adversarial Networks are known to require good hardware and time to train. Because of this, certain optimizations and standards have come to be so as to reduce the time for training in GANs. In this blog I will list a few of these tips that help create better GANs faster. Most of these come from books and videos such as Jason Brownlee’s General Adversarial Networks with Python.

The first tip starts with the latent space. The latent space is what defines the input dimensions for the generator part of the GAN model. This is typically created by a simple…

Arnav Kartikeya

A high school student interested in cognitive science and programming

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