Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

Learning M-Way Tree - Web Scale Clustering - EM-tree, K-tree, k-means, TSVQ, repeated k-means, bitwise clustering

Fast and precise comparison of genomes and metagenomes (in the order of terabytes) on a typical personal laptop

SetSketch: Filling the Gap between MinHash and HyperLogLog

ProbMinHash – A Class of Locality-Sensitive Hash Algorithms for the (Probability) Jaccard Similarity

Software for exploration of gene expression data from single-cell RNA sequencing.

Query-Aware LSH for Approximate NNS (PVLDB 2015 and VLDBJ 2017)

BagMinHash - Minwise Hashing Algorithm for Weighted Sets

Generate kmers/minimizers/hashes/MinHash signatures, including with multiple kmer sizes.

A fast high dimensional near neighbor search algorithm based on group testing and locality sensitive hashing

Query-Aware LSH for Approximate NNS (In-Memory Version of QALSH)

Point-to-Hyperplane NNS Beyond the Unit Hypersphere (SIGMOD 2021)

TreeMinHash: Fast Sketching for Weighted Jaccard Similarity Estimation

C++ program that, given a vectorised dataset and query set, performs locality sensitive hashing, finding either Nearest Neighbour (NN) or Neighbours in specified range of points in query set, using either Euclidian distance or Cosine Similarity.

Nearest neighbor search. Methods: LSH, hypercube, and exhaustive search. C++

C++ implementation of Locality-Sensitive Hashing over txt documents, using Jaccard Similarity.

Easy_Localization

similarity search and clustering algorithms for time-series represented as euclidean polygonal curves

ANN - Approximate Nearest Neighbors Index with Locality Sensitive Hashing and Hyper Cube projections for vectors and multi-dimensional data.

HSEARCH: fast and accurate protein sequence motif search and clustering