Diffusion
Generates data by learning to reverse a gradual noising process.
Überblick
A diffusion model learns to remove noise step by step, so that sampling starts from pure noise and arrives at a plausible sample. It solves the training instability of adversarial methods by replacing a two-player game with a single denoising objective. It exists because that objective is stable and covers the data distribution well, which is why it became the dominant approach for image generation.
Technologiegraph
Wie Diffusion mit dem übrigen Stack zusammenhängt.
Nutzt und hängt ab von
- Neural Network concept Algorithms Diffusion based on Neural Network High ✓ source
Genutzt von
- Image Generation application Applications Diffusion used by Image Generation High ✓ source
Werkzeuge
Software, die Diffusion implementiert oder integriert.
Frameworks
Alternativen
Vergleiche
Detaillierte Gegenüberstellungen mit den Alternativen oben.