hyperplane-tree
Web Components adapter for Hyperplane
Annoy.js is a 0-dependency Hyperplane (Binary) Search Tree, inspired by Spotify Annoy as described by <a href="https://erikbern.com/2015/10/01/nearest-neighbors-and-vector-models-part-2-how-to-search-in-high-dimensional-spaces.html" target="_blank">This B
Scaffolding for isomorphic coffeescript libraries
A ReactiveX based components system for Web Components
Model Context Protocol server for Shakudo Platform API with enhanced image builder tools
test for the intersection of convex polytopes in 2d or 3d, computing the minimum translation vector
LAPACK routine to apply a real elementary reflector `H = I - tau * v * v^T` to a real M by N matrix `C`.
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npm package to manage shakudo resources.
Hyperplane — a parameter-model-driven testing and orchestration system built on top of paramodel. hyperplane-specific sub-crates re-export through here as they land.
Hyperplane primitives for the RustUse geometry workspace
N-dimensional Euclidean geometry for Rust: points, vectors, lines, segments, hyperspheres, hyperplanes, AABBs, triangles, and a unified intersection API—all with const generics.
Secret-sharing primitives (Shamir, Blakley, ramp, VSS, CRT, visual, etc.) implemented directly from the original papers with no external dependencies.
geometric primitives: rays, hyper-planes, hyper-spheres, axis-aligned bounding boxes
Using Locality Sensitive hashing to find the nearest points to a query point in extremely high dimensional space.
Annoy-inspired Approximate Nearest Neighbors in Rust, based on LMDB and optimized for memory usage
K-dimensional tree space-partitioning data structure
An unofficial Rust implementation of MuVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings
A lightweight, in-memory vector index for approximate nearest neighbors using Locality-Sensitive Hashing
Project N-dimensional physics worlds into Bevy 3D rendering, with first-class 4D cross-section slicing (Miegakure-style). Bridge crate between symtropy-physics and Bevy.
An AI-native embedded database
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