[D] Question: Optimal D notation in Generative Adversarial Networks (GANs)

Web: https://www.reddit.com/r/MachineLearning/comments/sh5thk/d_question_optimal_d_notation_in_generative/

Hi

I am completely new to Computer Vision and how Deep Neural Networks work on images in general. In particular, I have questions on the Generative Network component of Adversarial Generative Network (GANs). There are some things that are left unexplained to me:

1. Optimal Discriminator is given by:

$D^*(x) = \frac{p_{data}(x)}{p_{data}(x) + p_G(x)}$

Based on source: https://deepgenerativemodels.github.io/notes/gan/ and https://jonathan-hui.medium.com/proof-gan-optimal-point-658116a236fb.

with $x \sim p_{data}(x)$ representing the sample of training images and $x \sim p_G(x)$ the sample of generated images. Therefore, …

gans machinelearning networks