Starting with Generative Models and Data Distributions
My notes comparing discriminative and generative models before checking tensor shapes and visualizing data.
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2025 Generative Models Intensive
My study sequence from generative-model foundations through autoregressive models, VAE, GAN, Pix2Pix, and diffusion.
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Autoregressive Factorization and MLE
Notes connecting joint-probability factorization, teacher forcing, log-likelihood, and cross entropy.
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VAE ELBO and Reparameterization
Notes on why the encoder predicts a mean and variance and how reconstruction and KL losses interact.
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From GANs to Pix2Pix
Notes connecting alternating generator and discriminator updates with Pix2Pix conditioning and L1 loss.
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From DDPM to Latent Diffusion and DiT
Notes connecting forward noise, reverse denoising, latent space, and a transformer backbone.
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