Official Implementation: Integrating Neural Operators with Diffusion Models for Improved Spectral Representation in Turbulence Modeling

Official Implementation: Integrating Neural Operators with Diffusion Models for Improved Spectral Representation in Turbulence Modeling

This repository contains the official implementation of our work,
"Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling,"
published in the Proceedings of the Royal Society A (PRSA).

🚀 Features

• Reproducible implementation of Neural Operators (NO) and Diffusion Models (DM) for turbulence modeling
• Python scripts for training on various turbulent flow problems
• Includes training, evaluation, and visualization scripts

📖 Reference

If you use this code, please consider citing our paper.

🛠 Installation & Usage

For setup instructions and usage details, refer to the README.md.

Full Changelog: v0.1.0-alpha...v1.0.0

Repository for "Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling"

This repository is associated with the research paper "Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling", which is currently under review. At this stage, the repository does not contain code. A future release will include the code and supplementary materials upon acceptance.