Yes estimating distance between distributions with single sample sounds irrelevant. I wonder if flow-based artefacts are sufficiently similar across models with the same FID, allowing us to learn the score predictive model. I may try later!

Agree! I wonder if some generation artefacts are signatures that allow to predict the FID score (suppose that they are present in almost all generated images by a given model)

PS: We also recently released a unified codebase for discrete diffusion, check it out!

𝕏 Thread : x.com/nkalyanv99/...
🔗 GitHub: github.com/nkalyanv99/...
📚 Docs: nkalyanv99.github.io/UNI-D2/

I use drum mic kits for punchier presentations

Then I’m counting on the sound engineer to engage

Sorry but it's getting pretty when leaving python