Training of Locally Optimized Product Quantization (LOPQ) models for approximate nearest neighbor search of high dimensional data in Python and Spark.

Some useful tips for faiss

Fast and memory-efficient clustering

Pure python implementation of product quantization for nearest neighbor search

⚡ A fast embedded library for approximate nearest neighbor search

Fast and memory-efficient ANN with a subset-search functionality

utils to use word embedding models like word2vec vectors in a PostgreSQL database

Implementation of vector quantization algorithms, codes for Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search.

PQ Fast Scan

Plugin to integrate approximate nearest neighbor(ANN) search with Elasticsearch

WSDM'22 Best Paper: Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval

Fast search algorithm for product-quantized codes via hash-tables

Generalized Product Quantization Network For Semi-supervised Image Retrieval - CVPR 2020

CIKM'21: JPQ substantially improves the efficiency of Dense Retrieval with 30x compression ratio, 10x CPU speedup and 2x GPU speedup.

Self-supervised Product Quantization for Deep Unsupervised Image Retrieval - ICCV2021

Fast C++ implementation of https://github.com/yahoo/lopq: Locally Optimized Product Quantization (LOPQ) model and searcher for approximate nearest neighbor search of high dimensional data.

Product Quantization k-Nearest Neighbors

product quantization image processing algorithm with matlab

[DEPRECATED] Baseline Project for Semantic Searching

A tiny approximate K-Nearest Neighbour library in Python based on Fast Product Quantization and IVF