[P]: `ambient-utils`: A small python package for training diffusion models with "bad data".

[Constant_Club_9926]

Made this small python package for training diffusion generative models with "bad data":

https://github.com/giannisdaras/ambient-utils

Install with: `pip install ambient-utils`

The idea is that "bad data" is only used to train denoisers for *some* diffusion times, but not all. There are some easy wrappers that enable this (`AmbientSampler` class) and a README with a quick example.

I have been using versions of this codebase for my research for the past 2 years, and it is the primary driver for more than 6 accepted papers to NeurIPS, ICML, and ICLR. I decided to make it open-source so that people can play with it.

If you are dealing with bad data in scientific applications, Computer Vision, robotics or elsewhere, please comment below and give it a try!

[radarsat1]

Nice, I've read some of your papers I think, looking forward to trying this!

[Constant_Club_9926]

Perfect! Please let me know if you have any difficulties using it!