Interested in trying out diffusion-based “neural simulators” for fluids yourselves? We’ve just added a notebook that let’s you get started with training and probabilistic inference right away: https://github.com/tum-pbs/autoreg-pde-diffusion/blob/main/acdm-demo.ipynb
The image above shows a few generated posterior samples for the (tough) transonic flow dataset. Alternatively, you can also directly run it in colab via this link: https://colab.research.google.com/github/tum-pbs/autoreg-pde-diffusion/blob/main/acdm-demo.ipynb
Note that this model loads a pre-trained diffusion model, and runs fine-tuning for 10 epochs. The full training would require ca. one day of runtime. Here’s also the temporal evaluation from the notebook:
