Diffusion
term_id: diffusion
Category: application_paradigms
Definition
Diffusion models are a class of generative AI that learn to reverse a stochastic process of adding noise to data. By training a neural network to predict and remove this noise step-by-step, they can generate high-quality, diverse samples such as images, audio, or text. These models have become state-of-the-art in creative tasks due to their stability and ability to produce realistic outputs compared to earlier GANs.
Summary
A generative modeling technique that creates data by reversing a gradual noising process to reconstruct clean samples.
Key Concepts
- Stochastic Process
- Noise Schedule
- Reverse Process
- Latent Space
Use Cases
- High-fidelity image generation
- Audio synthesis
- Drug discovery molecular design