Diffusion Models

Interactively explore how diffusion models add and remove noise to generate data, simulating the forward and reverse processes.

Diffusion Simulation

Educational Diffusion Sandbox

Explanation

  • Forward Process: Gradually adds noise to the data until it becomes pure noise.
  • Reverse Process: Neural network learns to remove noise, reconstructing the original data.
  • Score-based Models: Learn the gradient of the log-probability density function of the data.
Click Forward Noise +1 to add noise, Reverse Denoise to recover the pattern, and Reset to restart.
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