There are 4 repositories under nearest-neighbors topic.
Benchmarks of approximate nearest neighbor libraries in Python
For extensive instructor led learning
An easy-to-use Python library for processing and manipulating 3D point clouds and meshes.
Nearest Neighbor Search with Neighborhood Graph and Tree for High-dimensional Data
TensorFlow Similarity is a python package focused on making similarity learning quick and easy.
RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.
Python implementation of KNN and DTW classification algorithm
High performance nearest neighbor data structures (KDTree and BallTree) and algorithms for Julia.
Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].
A scalable nearest neighbor search library in Apache Spark
Fast Near-Duplicate Image Search and Delete using pHash, t-SNE and KDTree.
Improving Generalization via Scalable Neighborhood Component Analysis
Performance evaluation of nearest neighbor search using Vespa, Elasticsearch and Open Distro for Elasticsearch K-NN
A lightweight and efficient Python Morton encoder with support for geo-hashing
The code repository for the paper: Peijie et al., Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering. IEEE TKDE, 2023.
Compressing Representations for Self-Supervised Learning
Python wrapper around C++ utilities for computing neighbors and local geometric features of a point cloud
R package providing fast nearest neighbour search (wraps ANN library)
A full-featured indoor positioning system that was developed during my master thesis. It has a javascript based rich UI and has a server-client architecture.
rust implementation of octree algorithm for nearest neighbor search in 3D space
A fast, accurate, and modularized dimensionality reduction approach based on diffusion harmonics and graph layouts. Escalates to millions of samples on a personal laptop. Adds high-dimensional big data intrinsic structure to your clustering and data visualization workflow.
Efficient approximate k-nearest neighbors graph construction and search in Julia
Approximate Nearest Neighbor search using reduced-rank regression, with extremely fast queries, tiny memory usage, and rapid indexing on modern vector embeddings.
This is our standard library for nonlinear analysis. Many of these functions are the same we use in our services. We do have additional methods that are not public but could be made available in a future release. If you are interested in learning more, attending our workshops or webinars or using our data analysis services please contact bmchnonan@unomaha.edu.
All the code for a series of Medium articles on Approximate Nearest Neighbors
Simple and efficient Python package for modeling d-dimensional Bravais lattices in solid state physics.
A framework for building (and incrementally growing) graph-based data structures used in hierarchical or DAG-structured clustering and nearest neighbor search
Misc Statistics and Machine Learning codes in R