Noise Schedule

Diffusion performed in latent space for efficiency.

Model that compresses input into latent space and reconstructs it.

Autoencoder using probabilistic latent variables and KL regularization.

Two-network setup where generator fools a discriminator.

Models that learn to generate samples resembling training data.

Generative model that learns to reverse a gradual noise process.

Diffusion model trained to remove noise step by step.

Learns the score (∇ log p(x)) for generative sampling.