Thermodynamic Diffusion: A Minimal DDPM Implementation

Key Points

• The aim is to provide a simple implementation of a diffusion model inspired by thermodynamics to enhance clarity and coherence in sample generation.
• Implemented a denoising diffusion probabilistic model (DDPM) guided by thermodynamic concepts.
• Utilized a learned constraint field to navigate through a low-energy manifold during the diffusion process.
• Focused on score matching objectives to align model outputs with target distributions.
• Produced more coherent and higher-quality samples compared to traditional methods.
• Demonstrated the core mechanics of diffusion models effectively.
• Provided a foundational approach that can be further developed for advanced generative tasks.

Abstract