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Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk
Header-only C++/python library for fast approximate nearest neighbors
Nearest Neighbor Search with Neighborhood Graph and Tree for High-dimensional Data
Graph-structured Indices for Scalable, Fast, Fresh and Filtered Approximate Nearest Neighbor Search
fast library for ANN search and KNN graph construction
A library of algorithms for approximate nearest neighbor search in high dimensions, along with a set of useful tools for designing such algorithms.
[SIGMOD 2024] RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search
[SIGMOD 2023] High-Dimensional Approximate Nearest Neighbor Search: with Reliable and Efficient Distance Comparison Operations
Approximate Nearest Neighbor search using reduced-rank regression, with extremely fast queries, tiny memory usage, and rapid indexing on modern vector embeddings.
This is the implementation of the Hierarquical Clustering-based Nearest Neighbor Graphs
A new query hardness measure for graph-based ANN indexes. Build unbiased workloads with this hardness to see the actual performance of your ANN indexes.