Today at JHU I went to the joint group meeting of Jeremias Sulam (JHU) and Soledad Villar (JHU) in which Jacopo Teneggi (JHU) showed guarantees on correctness for some diffusion-based de-noising schemes for images. The quarantees are a bit weak, because it is hard to put a hard boundary on coverage in image space! But essential for medical applications (the illustrated domain). I have to say, it was nice to see a rigorous approach to errors from machine-learning methods. I think this is necessary for our uses in cosmology, where we are expecting machine-learning emulators to be as accurate as simulations!?!
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