Graph Algorithms
Showing 36 of 85 projects
A comprehensive collection of JavaScript implementations of algorithms and data structures with detailed explanations.
Minimal, clean, and well-documented implementations of data structures and algorithms in Python 3.
Network Analysis in Python
A comprehensive set of numeric libraries for Go, providing matrices, statistics, optimization, and graph algorithms.
A collection of classic algorithms and data structures implemented as single-header C++ files with demo programs.
A transactional, relational-graph-vector database that uses Datalog for query, designed as the hippocampus for AI.
A fast, flexible graph data structure library for Rust with multiple graph types and built-in algorithms.
A highly extensible JavaScript library for rendering interactive graphs with support for multiple layout algorithms and rendering engines.
A collection of Ruby implementations for common algorithm problems, focused on technical interview preparation.
A free Java library providing mathematical graph-theory objects and algorithms.
A curated list of community detection research papers with implementations.
A collection of well-known computer science algorithms and data structures implemented in Objective-C for educational purposes.
A collection of GPU-accelerated graph analytics libraries for creating, manipulating, and executing scalable graph algorithms.
A Swift framework providing implementations of common data structures and algorithms with educational examples.
A curated collection of research papers and software for explainable graph machine learning and reasoning.
Awesome Procedures On Cypher for Neo4j - codenamed "apoc" If you like it, please ★ above ⇧
A high-performance Python graph library implemented in Rust for general-purpose graph algorithms.
A robust and multipurpose Graph object for JavaScript and TypeScript, supporting various graph types with a unified interface.
A Python interface for the igraph library, enabling fast creation, manipulation, and analysis of large graphs and networks.
A DataFrame-based graph processing library for Apache Spark, enabling scalable graph analytics and algorithms.
A graph library for Clojure providing immutable graph data structures and algorithms.
A comprehensive collection of algorithm implementations in Go, based on the CLRS textbook.
A comprehensive Swift library for creating and manipulating weighted, unweighted, directed, and undirected graphs with built-in algorithms.
A Go library providing efficient implementations of fundamental graph algorithms and data structures.
A Go package implementing graph data structures and algorithms with comprehensive tutorials and visualizations.
A header-only C++ library for graph representation and algorithms, designed as a modern alternative to Boost Graph Library.
A Python library providing a comprehensive collection of graph sampling algorithms for NetworkX and NetworKit.
A modern C++ toolkit for text retrieval and analysis, featuring indexing, ranking, topic modeling, classification, and language models.
An optimized graph analysis package for Julia, providing simple concrete graph types and an API for custom implementations.
A lightweight, in-memory graph data structure library for JavaScript with event-driven updates.
A tidy API for graph manipulation in R, providing dplyr verbs and igraph algorithms for network analysis.
A machine learning integrations library for TypeDB, enabling graph algorithms and Graph Neural Networks on strongly-typed graph data.
A comprehensive .NET library providing sophisticated algorithms and data structures like graphs, priority queues, and undo-redo functionality.
A Neo4j extension for document and text classification using graph-based hierarchical pattern recognition.
A high-performance Rust library for graph algorithms, built on a parallel CSR data structure for large-scale graphs.
A Python meta-library for community detection in complex networks, implementing algorithms, fitness functions, and visualization.
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