Diffusion
Generates data by learning to reverse a gradual noising process.
Обзор
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.
Граф технологий
Как Diffusion связана с остальным стеком.
Использует и зависит от
- Neural Network concept Algorithms Diffusion based on Neural Network High ✓ source
Используется в
- Image Generation application Applications Diffusion used by Image Generation High ✓ source
Инструменты
ПО, которое реализует Diffusion или интегрируется с ним.
Frameworks
Альтернативы
Сравнения
Подробные сопоставления с альтернативами выше.