Found 33 packages
Natural Neighbor 2D Interpolator based on Delanuay tesselation
C# library for fast approximate nearest neighbours search using Hierarchical Navigable Small World graphs. Fork from original at https://github.com/microsoft/HNSW.Net, adds support for incremental build and MessagePack serialization.
HNSWIndex provides a high-performance, approximate nearest-neighbor search solution using the HNSW data structure. It supports custom distance metrics, efficient searching with concurrency, and configurable parameters to balance speed, recall, and memory usage. Perfect for .NET applications that require fast similarity lookups (e.g., image retrieval, recommendation systems, or vector-based search).
HNSW provides a high-performance, approximate nearest-neighbor search solution using the HNSW data structure. It supports custom distance metrics, efficient searching with concurrency, and configurable parameters to balance speed, recall, and memory usage. Perfect for .NET applications that require fast similarity lookups (e.g., image retrieval, recommendation systems, or vector-based search).
Provide a helper to get the list of all US states and list of neighboring states for each state
hnswlib: Header-only C++ library for fast approximate nearest neighbors
Mikrotik Neighbor Discovery Protocol - Network Discovery
An instanced, dedicated ThreadPool for eliminating "noisy neighbor" problems on the CLR ThreadPool
FLANN is a library for performing fast approximate nearest neighbor searches in high dimensional spaces.
Contains Support Vector Machines, Decision Trees, Naive Bayesian models, K-means, Gaussian Mixture models and general algorithms such as Ransac, Cross-validation and Grid-Search for machine-learning applications. This package is part of the Accord.NET Framework.
SPTAG (Space Partition Tree And Graph) is a library for large scale vector approximate nearest neighbor search scenario released by Microsoft Research (MSR) and Microsoft Bing.
Useful structures for image processing such as mappings, near neighbor field, vector, interval, etc.
Neighborly is an open-source vector database that efficiently stores and retrieves vector data. Built with .NET, it provides functionality for handling high-dimensional vectors, making it ideal for machine learning, data science applications, and more.
The $1 Unistroke Recognizer is a 2-D single-stroke recognizer designed for rapid prototyping of gesture-based user interfaces. In machine learning terms, $1 is an instance-based nearest-neighbor classifier with a Euclidean scoring function, i.e., a geometric template matcher. $1 is an extension of the proportional shape matching approach used in SHARK2, which itself is an adaptation of Tappert's elastic matching approach with zero look-ahead.
Dotnet wrapper over faisslib vector store (see https://github.com/facebookresearch/faiss). Currently only available for Windows x64. (Support for other platforms is possible).
Generic implementation of A* pathfinding algorithm for which you can provide different implementations of Distance Calculation algorythms, neighbor/space topology provider, pathable nodes provider, and struct representing node coordinates.
SIMD-accelerated vector similarity search for Sharc. Zero-copy BLOB decode, cosine/euclidean/dot product distance via TensorPrimitives, top-K nearest neighbor with metadata pre-filtering.
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