algorithms-math

346 bookmarks · page 1 of 7
2026-10-09 · htmx.org

htmx ~ Yes, and...

In this essay, Carson Gross discusses his advice to young people interested in computer science worried about the future given the advancements in AI.

2026-09-16 · gegell.github.io

Reversing Factorio's RNG

This post details how Factorio's random number generation works, how it can be reversed and how I used that knowledge to predict and manipulate the RNG with pure in‑game mechanics.

How is it possible for a deterministic game like Factorio to have a random mechanic?
PRNG
2026-03-23 · marktechpost.com

How BM25 and RAG Retrieve Information Differently? - MarkTechPost

When you type a query into a search engine, something has to decide which documents are actually relevant — and how to rank them. BM25 (Best Matching 25), the algorithm powering search engines like Elasticsearch and Lucene, has been the dominant answer to that question for…

The clever part is that BM25 doesn’t reward keyword stuffing
saturation
2025-10-24 · tannerhelland.com

Image Dithering: Eleven Algorithms and Source Code

Dithering is still a surprisingly applicable technique, not just for practical reasons (such as preparing a full-color image for output on a non-color printer), but for artistic reasons as well. Dithering also has applications in web design, where it is a useful technique for…

Dithering Sticky notes:Adding white noise to reduce errors from spurious signals
dithering is fundamentally about error diffusion.
2025-10-16 · arxiv.org

An Introduction to Multisets

Multisets are sets that allow repetition of elements. As such, multisets pave the way to a number of interesting possibilities of theoretical and applied nature. In the present work, after revising the main aspects of traditional sets, we introduce some of the main concepts and…

Multisets are sets that allow repetition of elements.
generalization to take into account vectors and matrices
2025-10-12 · johndcook.com

Generate random points inside a sphere

Generating random points inside a sphere of any dimension.

The customary way to generate points on a sphere in n dimensions is to generate points from an n-dimensional normal (Gaussian) distribution and normalize by dividing by the length. And the way to generate samples from an n-dimensional normal is simply to generate a list of n one-dimensional normals…
Instead, the thing to do is to set