improved-diffusion is an open source implementation of diffusion probabilistic models created by OpenAI. These models, also known as score-based generative models, are a class of generative models that have shown strong performance in producing high-quality synthetic data such as images. The repository provides code for training and sampling diffusion models with improved techniques that enhance stability, efficiency, and output fidelity. It includes scripts for setting up training runs, generating samples, and reproducing results from OpenAI’s research on diffusion-based generation. The implementation is intended for researchers and practitioners who want to explore the theoretical and practical aspects of diffusion models in deep learning. By making this code available, OpenAI provides a foundation for further experimentation and development in generative modeling research.
Features
- Open source implementation of diffusion probabilistic models
- Supports training and sampling workflows for generative modeling
- Includes improvements for stability and output quality
- Reproducible experiments aligned with OpenAI research
- Provides scripts and tools for managing training runs
- Useful for exploring generative modeling with diffusion methods