NCA-GENM Exam Dumps | Consider the following scenario: You're training a GAN for generating high-resolution images (e.g., 1024x1024).

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Question 180/192

Consider the following scenario: You're training a GAN for generating high-resolution images (e.g., 1024x1024). You notice that the training process is unstable, with the generator and discriminator constantly oscillating. Which of the following architectural modifications and training techniques could help stabilize the training process?

A. Replacing standard convolutional layers with transposed convolutional layers in the generator.

B. Using Wasserstein GAN (WGAN) with gradient penalty (GP).

C. Applying batch normalization in both the generator and discriminator.

D. Increasing the learning rate of both the generator and discriminator.

E. Using ReLU activation functions in the discriminator.

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