nearest-neighbors
There are 251 repositories under nearest-neighbors topic.
erikbern/ann-benchmarks
Benchmarks of approximate nearest neighbor libraries in Python
edyoda/data-science-complete-tutorial
For extensive instructor led learning
fwilliams/point-cloud-utils
An easy-to-use Python library for processing and manipulating 3D point clouds and meshes.
yahoojapan/NGT
Nearest Neighbor Search with Neighborhood Graph and Tree for High-dimensional Data
tensorflow/similarity
TensorFlow Similarity is a python package focused on making similarity learning quick and easy.
markdregan/K-Nearest-Neighbors-with-Dynamic-Time-Warping
Python implementation of KNN and DTW classification algorithm
rapidsai/raft
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.
KristofferC/NearestNeighbors.jl
High performance nearest neighbor data structures (KDTree and BallTree) and algorithms for Julia.
vc1492a/PyNomaly
Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].
netrasys/pgANN
Fast Approximate Nearest Neighbor (ANN) searches with a PostgreSQL database.
LinkedInAttic/scanns
A scalable nearest neighbor search library in Apache Spark
arborx/ArborX
Performance-portable geometric search library
umbertogriffo/fast-near-duplicate-image-search
Fast Near-Duplicate Image Search and Delete using pHash, t-SNE and KDTree.
microsoft/snca.pytorch
Improving Generalization via Scalable Neighborhood Component Analysis
jobergum/dense-vector-ranking-performance
Performance evaluation of nearest neighbor search using Vespa, Elasticsearch and Open Distro for Elasticsearch K-NN
rapidsai/cuvs
cuVS - a library for vector search and clustering on the GPU
trevorprater/pymorton
A lightweight and efficient Python Morton encoder with support for geo-hashing
PeiJieSun/NESCL
The code repository for the paper: Peijie et al., Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering. IEEE TKDE, 2023.
HaojiHu/TIFUKNN
kNN-based next-basket recommendation
UMBCvision/CompRess
Compressing Representations for Self-Supervised Learning
segasai/q3c
PostgreSQL extension for spatial indexing on a sphere
eddelbuettel/rcppannoy
Rcpp bindings for Annoy
davpinto/fastknn
Fast k-Nearest Neighbors Classifier for Large Datasets
jefferislab/RANN
R package providing fast nearest neighbour search (wraps ANN library)
gchq/annchor
Fast k-NN graph construction for slow metrics
patrickfav/indoor-positioning
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.
davisidarta/dbMAP
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.
drprojects/point_geometric_features
Python wrapper around C++ utility to compute local geometric features of a point cloud
stephenleo/adventures-with-ann
All the code for a series of Medium articles on Approximate Nearest Neighbors
dillondaudert/NearestNeighborDescent.jl
Efficient approximate k-nearest neighbors graph construction and search in Julia
Dentrax/Data-Mining-Algorithms
Data Mining Algorithms with C# using LINQ
jchambers/jvptree
A generic vantage point tree (vp-tree) implementation in Java
jchambers/jeospatial
A memory-resident geospatial index library for Java
nmonath/graphgrove
A framework for building (and incrementally growing) graph-based data structures used in hierarchical or DAG-structured clustering and nearest neighbor search
tirthajyoti/R-stats-machine-learning
Misc Statistics and Machine Learning codes in R
Nonlinear-Analysis-Core/NONANLibrary
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.