GAN 5: Conditional GAN and Pix2Pix
How Conditional GANs extend vanilla GANs to generate class-specific samples, and how Pix2Pix does image-to-image translation.
Blog
Writing on Voice AI, speech research, and machine learning.
GAN 4: Deep Convolutional GAN (DCGAN) on SVHN
Implementing DCGAN with CNNs, batch normalization, and transposed convolutions to generate Street View House Numbers.
GAN 2: The Game Theory Behind Generator and Discriminator
How the adversarial game between Generator and Discriminator works, and why equilibrium matters.
GAN 3: Implementing a Linear GAN on MNIST in PyTorch
Step-by-step PyTorch implementation of a vanilla GAN trained on MNIST — data loading, Discriminator, Generator, training loop.
GAN 1: Introduction to Generative Adversarial Networks
What GANs are, how they work, and some remarkable recent research — StackGAN, iGAN, Pix2Pix.