Charlie Loyd @vruba@everything.happens.horse

@dpiponi So cool – the kind of thing I would ask my (math major) mom about as a kid and she’d say “Sure, in theory, maybe one day when computers are better.”

Two brainstorms just in case they’re interesting:

1. I’ve been reading about shearlets, which are near-optimal at representing the wavefront set, and I can feel things in the back of my brain churning here. (E.g., the “fractal” looks a bit like a noiselet.)

2. Would the results be subjectively different if trained with a little noise?

I’m going to throw my coffee on the next mathematician I meet.

It’s pretty old-fashioned now. The vanilla DWT, the Tudor-era entropy coder – with only admiration for what it was in 2003, no one would propose a new format like ICER today. But it’s interesting in itself and as a what-if. (What if JPEG 2000 were designed for normal people, basically.)

I was just saying to a friend that JPEG 2000 never succeeded in supplanting JPEG outside a few high-end niches (mapping, archives, medical imaging) due to a scope-crept, complex, IP-unclear, and generally unappealing-to-nonspecialist-developers design, but I think there’s an alternate history not too far away in the multiverse where someone adapted ICER into an OS and browser-supported JPEG replacement in, like, 2005.

https://github.com/TheRealOrange/icer_compression is pretty neat – a mostly complete implementation of ICER, a wavelet-based, error-resilient image compression format designed by NASA 20+ years ago for Spirit and Opportunity.

@secretasianman Their podcasters are terrible.

Based on informal tinkering and reading. Happy to discuss, within reason.

1. QKV attention transformers work but are gross – O(n²) and equivariance problems – and will not last.

2. Most – not all! – learned convolutions are wasted and should be replaced by fixed bases or frames, or at least grouped convolutions.

3. Diffusion and flow training approaches are immature but way more elegant than x→y training.

5. MMA regularization is good.

One of my favorite things on the Internet is when you watch a “Columbo” clip and there’s a comment where someone describes the concept of Columbo at a second-grade level and is massively upvoted for it. This sounds wry and ironical but I do honestly enjoy it.

I’m tinkering with something where shearlets are very clearly The Right Tool For The Job. There is one pytorch library implementing them in what looks like a good way. Its last commit was 3 years ago and it’s not on PyPI; turns out you have to compile it locally against the CUDA SDK. Using it would instantly make my project unportable. I’m not complaining about the author of the library – if anything, I’m grateful to them. But I’m certainly complaining about the situation.

Waking up early, going on a walk, making breakfast, and then spending two hours meditating on how much I wish someone would write some good, differentiable, richly featured wavelet libraries in python.