Some useful tips for faiss

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

Pure python implementation of product quantization for nearest neighbor search

Fast and memory-efficient clustering

⚡ 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

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

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

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

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

🔥ImageFolder: Autoregressive Image Generation with Folded Tokens

PQ Fast Scan

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

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

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

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.

Quick ADC

Product Quantization k-Nearest Neighbors

Inverted file system for billion-scale ANN search