This is amazing. Congrats on the project! I initially started learning rust a few years ago specifically for it's support for compiling to webassembly, as I found it so interesting. This project and the discussion on the post makes me want to get back to it :D
Yeah - I totally agree. Some others on the thread pointed it out as well. I ended up replacing it with a table additionally having the error percentages.
Thanks for the fair critique! I've also mentioned your username in the edit logs at the end of the blog if you don't mind.
That's a major claim. The only thing different in this blog post from my others is that I've embedded an executable python notebook in an iframe.
It's a marimo notebook that runs code using WASM in your browser. That project is open source too, with no exploit as far as I know.
I would be happy to be wrong on this one. But I've gotten two pretty convincing threat notifications when visiting the page from the Sentinel One antivirus platform saying that my msedge process had been compromised by a known exploit.
I'll try to get more details.
I should note, I do not believe the site is malicious, but i am worried about 3rd party compromise of the site without the owner's knowledge
I see, that's strange. Yeah, feel free to share the details/logs with me - you can open an issue on my blog's repo with the relevant details and system info.
However, I'm still suspecting it's something specific to your antivirus not knowing what to do with WASM code(which is used on this page). I found something similar on Reddit: https://www.reddit.com/r/eaglercraft/s/heVtPy60lG. I wonder if that's the issue.
You're totally correct, my writeup in that section definitely was not clear. I've updated the blog, hopefully it's better. I've also given you a shoutout in the end of the post in my edit log, if that's cool with you
Sure, thanks. I also saw this sentence, which was not there in the last version (I think):
> That is to say, with n nodes, gaussian integration will approximate your function's integral with a higher order polynomial than a basic technique would - resulting in more accuracy.
This is not really the case, Gaussian integration is still just interpolation on n nodes, but the way of choosing the nodes increases the integration's exactness degree to 2n-1. It's actually more interesting that Gaussian integration does not require any more work in terms of interpolation, but we just choose our nodes better. (Actually, computing the nodes is sometimes more work, but we can do that once and use them forever.)
Thats a cool algorithm!! I couldnt find resources on how it might be used to compute distance functions (though it seems like it can). It seems to be for approximating voronoi diagrams.
The two problems are highly related, which is why it can do both. At the end of the algorithm, you have a per-pixel assignment of the (approximately) closest seed pixel. If you want a voronoi diagram, then you color each pixel according to the identify of its seed pixel. If you want a distance function, then you color it with the distance to that pixel.
