Explore machine learning papers and reviews related to generativemodels. Find insights, analysis, and implementation details.
How GANs frame generative modeling as a two-player minimax game: a generator turns noise into samples while a discriminator learns to tell real from fake, driving the generator toward the true data distribution.
How the variational autoencoder turns an autoencoder into a generative model: an encoder predicts a Gaussian latent distribution, the reparameterization trick makes sampling differentiable, and the ELBO balances reconstruction against a KL prior.