@Eamon1916 So glad they skipped 3k
Carlos
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⟨ Machine Learning | Physics ⟩ and other stuff too
@pbloem Also, I'd love to hear more from the experts what their takes are on this paper. I think it will be talked about soonish in the Eleuther AI Diffusion Reading Group (https://github.com/tmabraham/diffusion_reading_group) .
@pbloem It's a lovely paper! A take I've seen (and enjoy) is that perhaps the name "step-by-step-dedegradation" is a better name than "diffusion models."
I still really enjoy that there are so many insights of other fields that the usual "uncorrelated Gaussian pixel-wise noise" has connections with so many other areas of Maths & physics that allows one to, say, have a good starting guess of hyperparameters (the noise schedules!) but also you can forget all of that and it just... still works :)
@TedUnderwood Finally went around to reading this, good stuff!
@nsaphra I've been on and off, but recently took a probability class with Machine Learning and it was very very pretty. I advocate this path
@chrisoffner3d There are some forks of Mastodon (and more specifically, its front end? I wanna say... but maybe it requires the backend to play nicely) that allow for search and/or search for user's posts.
But yeah, it's very frustating, even if Twitter search is also bad
@asayeed Kid named people without inner monologue:
@tess Reminds me to what happened to Infinity Train.
Digital Hoarders keep winning.
@manifest_irony @briankrebs only accepted in the US though