Search Results for "graph algorithm"
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Showing 72 open source projects for "graph algorithm"
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ngraph.path
Path finding in a graph
ngraph.path is a JavaScript library that implements efficient pathfinding algorithms for graphs, primarily designed to compute shortest paths in weighted or unweighted networks. It provides a clean API for constructing graph models, assigning weights to edges, and querying for optimal routes between nodes, making it useful for routing, games, maps, and network optimization. The library includes several algorithm implementations such as A*, Dijkstra’s, and breadth-first search, each suited to different types of graph structure and performance needs. It can be integrated with visualization libraries like VivaGraphJS to animate or highlight computed paths in a rendered graph, enabling interactive routing features. ... -
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The Algorithms - C++ #
Collection of various algorithms in mathematics, machine learning
TheAlgorithms/C-Plus-Plus is a large open-source repository that collects implementations of many classic algorithms and data structures written in the C++ programming language. The project is part of the broader “The Algorithms” initiative, which maintains algorithm implementations in several programming languages to support education and knowledge sharing. Within the C++ repository, contributors implement algorithms across a wide range of fields including sorting, graph theory, number theory, machine learning, cryptography, and data structures. Each implementation is designed to be readable and well documented so that learners can understand the logic and structure behind each algorithm. -
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HugeGraph
A graph database that supports more than 100+ billion data
...Not only supports Gremlin graph query language and RESTful API but also provides commonly used graph algorithm APIs. To help users easily implement various queries and analyses, HugeGraph has a full range of accessory tools, such as supporting distributed storage, data replication, scaling horizontally, and supports many built-in backends of storage engines. -
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Torch Pruning
DepGraph: Towards Any Structural Pruning
...The library focuses on reducing the size and computational cost of neural networks by removing redundant parameters and channels while maintaining model performance. It introduces a graph-based algorithm called DepGraph that automatically identifies dependencies between layers, allowing parameters to be pruned safely across complex architectures. This dependency analysis makes it possible to prune large networks such as transformers, convolutional networks, and diffusion models without breaking the computational graph. -
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amrlib
A python library that makes AMR parsing, generation and visualization
...A SpaCy extension that allows direct conversion of SpaCy Docs and Spans to AMR graphs. Sentence to Graph alignment routines FAA_Aligner (Fast_Align Algorithm), based on the ISI aligner code detailed in this paper. RBW_Aligner (Rule Based Word) for a simple, single token to single node alignment. -
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JavaScript Algo and Data Structures
Algorithms and data structures implemented in JavaScript
javascript-algorithms is an open source repository by Oleksii Trekhleb that provides implementations of algorithms and data structures in JavaScript. Each algorithm includes explanations, complexity analysis, and references for further reading, making it both a coding resource and a study guide. The repository covers topics such as sorting, searching, graph algorithms, cryptography, and data structures like linked lists, stacks, and queues. It is designed to help developers understand algorithm fundamentals and practice problem-solving with JavaScript. ... -
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LeetCode Master
About "Code Thoughts" LeetCode Practice Guide: 200 classic questions
...The repository contains detailed explanations, categorized problem sets, and step-by-step reasoning behind solutions, making it an effective study companion for developers preparing for technical interviews. Problems are grouped by topic—such as arrays, linked lists, dynamic programming, greedy algorithms, and graph theory—so learners can focus on specific areas systematically. Each solution is accompanied by clear commentary to explain the thought process, algorithm design, and complexity analysis. The project is continuously updated and widely used by learners as both a reference and a roadmap to progress from beginner to advanced LeetCode practice. ... -
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DynamicHMC
Implementation of robust dynamic Hamiltonian Monte Carlo methods
Implementation of robust dynamic Hamiltonian Monte Carlo methods in Julia. In contrast to frameworks that utilize a directed acyclic graph to build a posterior for a Bayesian model from small components, this package requires that you code a log-density function of the posterior in Julia. Derivatives can be provided manually, or using automatic differentiation. Consequently, this package requires that the user is comfortable with the basics of the theory of Bayesian inference, to the extent... -
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Pythonic Data Structures and Algorithms
Minimal examples of data structures and algorithms in Python
The Pythonic Data Structures and Algorithms repository by keon is a hands-on collection of implementations of classical data structures and algorithms written in Python. It offers working, often well-commented code for many standard algorithmic problems — from sorting/searching to graph algorithms, dynamic programming, data structures, and more — making it a valuable resource for learning and reference. For students preparing for technical interviews, self-learners brushing up on fundamentals, or developers wanting to understand algorithm internals, this repository provides ready-to-run examples, and can serve as a sandbox to experiment, benchmark, or adapt code. ... -
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Go Recipes
Collection of handy tools for Go projects
Visualize the distribution of code coverage in your project. This helps to identify code areas with high and low coverage. Useful when you have a large project with lots of files and packages. This 2D image-hash of your project should be more representative than a single number. For each module, the node representing the greatest version (i.e., the version chosen by Go's minimal version selection algorithm) is colored green. Other nodes, which aren't in the final build list, are colored grey... -
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Vald
Vald. A Highly Scalable Distributed Vector Search Engine
Vald is a highly scalable distributed fast approximate nearest neighbor dense vector search engine. Vald is designed and implemented based on the Cloud-Native architecture. It uses the fastest ANN Algorithm NGT to search for neighbors. Vald has automatic vector indexing and index backup, and horizontal scaling which is made for searching from billions of feature vector data. Vald is easy to use, feature-rich and highly customizable as you needed. Usually, the graph requires locking during indexing, which causes stop-the-world. But Vald uses distributed index graphs so it continues to work during indexing. ... -
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AI_Tutorial
A selection of learning materials, search, recommendation, advertising
AI_Tutorial is a large curated repository that aggregates high-quality learning resources related to artificial intelligence, machine learning, deep learning, natural language processing, and data engineering. The project functions as a centralized knowledge base designed to help engineers and researchers discover tutorials, technical articles, algorithm explanations, and architecture discussions from across the AI ecosystem. Rather than focusing on a single framework or course, the repository collects materials from many sources such as open-source projects, technical blogs, research papers, and industry engineering posts. The curated content includes topics like recommendation systems, search engine architecture, neural networks, graph neural networks, and modern deep learning techniques. ... -
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TorchQuantum
A PyTorch-based framework for Quantum Classical Simulation
A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers. Researchers on quantum algorithm design, parameterized quantum circuit training, quantum optimal control, quantum machine learning, and quantum neural networks. Dynamic computation graph, automatic gradient computation, fast GPU support, batch model terrorized processing. -
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Bifurcum
Software to run through a directional graph.
This software runs through a directional graph and writes the paths it found as test specifications. It has a simple algorithm (Deep First Search with modifications) and allows sorting children before traversing. This application sums up the authors 4-years experience when programming a commercial tool for graph traversing (which used a much more advanced algorithm) and coaching its users. -
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Hypercube
Graph visualizing tool
Hypercube is a tool for visualizing DOT (graphviz), GML, GraphML, GXL and simple text-based graph representations as SVG and EPS images. Hypercube comes with a Qt based GUI application and a Qt-independent command-line tool. It uses a simulated annealing algorithm to lay out the graph, that can be easily parameterized to achieve the desired look. The main development goals are portability and easy usage rather than high performance and complexity. -
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Metatheory.jl
General purpose algebraic metaprogramming
Metatheory.jl is a general purpose term rewriting, metaprogramming and algebraic computation library for the Julia programming language, designed to take advantage of the powerful reflection capabilities to bridge the gap between symbolic mathematics, abstract interpretation, equational reasoning, optimization, composable compiler transforms, and advanced homoiconic pattern matching features. The core features of Metatheory.jl are a powerful rewrite rule definition language, a vast library of functional combinators for classical term rewriting and an e-graph rewriting, a fresh approach to term rewriting achieved through an equality saturation algorithm. Metatheory.jl can manipulate any kind of Julia symbolic expression type, as long as it satisfies the TermInterface.jl. -
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The Algorithms - C #
Collection of various algorithms in mathematics, machine learning
...The project is part of the larger “The Algorithms” initiative, which aims to create educational resources by implementing algorithms in multiple programming languages. Within the C repository, contributors implement algorithms from many areas of computer science including sorting, searching, graph processing, mathematics, machine learning, and numerical methods. Each algorithm implementation is written to be readable and well documented so that students and developers can understand how the algorithm works internally. The repository is designed primarily as an educational resource that helps programmers study algorithm design and computational thinking. ... -
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javascript-algorithms
JavaScript implementations of computer science algorithms
javascript-algorithms is a repository that implements a comprehensive collection of classic data structures and algorithmic solutions in JavaScript — including sorting, searching, graph algorithms, dynamic programming, and more. It serves as a learning and reference resource for developers wanting to understand how standard algorithms can be expressed in JavaScript, bridging the gap between theoretical algorithm knowledge and practical implementation usable in web or Node.js contexts. Because algorithms are implemented in a language (JavaScript) many developers use daily, the repo becomes especially useful for students, interview-preparation candidates, or anyone wanting to learn algorithmic thinking without switching languages. ... -
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Jadecy
Java lib to compute (code) deps, SCCs, and cycles (Johnson algorithm).
Jadecy (Java Dependencies and Cycles) is a Java library to compute dependencies (elements depended on, or depending), strongly connected components, and cycles, in general directed graphs, or classes or packages dependencies graphs parsed from class files (major version <= 52, else does best effort). It uses Tarjan's algorithm for SCCs computation, and Johnson's algorithm for exhaustive cycles computation, with continuations instead of recursion, which allows to handle large graphs (< 2^31 vertices). Since version 1.1, can also compute shortest cycles covering all edges of SCCs. Usage from command line is also possible but with reduced flexibility (cf. ... -
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HipMer
A High performance distributed memory assembler for big genomic data
...The single-genome assembly implementation is a high-performance parallelization and port of the Meraculous assembler (http://jgi.doe.gov/data-and-tools/meraculous/). The MetaHipMer extension is a recent addition to HipMer that is geared to large metagenomes and leverages iterative kmer sizes and a specialized scaffolding algorithm to produce increased contiguity and accuracy in metagenomic assemblies. It is able to reconstruct rRNA elements via a separate algorithm which relies on reference SSU and LSU Hidden Markov Models to help traverse the contig graph around ribosomal RNA regions. For more information and publications visit the HipMer Portal (http://portal.nersc.gov/project/hipmer/) MetaHipMer is one component of the ExaBiome project (https://sites.google.com/lbl.gov/exabiome/home), part of the Exascale Computing Project: https://www.exascaleproject.org/ -
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gml4gtk
small console GML or graphviz DOT graph viewer
directed graph layout program for GML (Graph-Markup-Language) graph or partial graphviz DOT graph -
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BifurcumLib
A library for running through a directional graph.
This is the library for the project Bifurcum. It does all the work. It has a simple algorithm (Deep First Search with modifications) and allows sorting children before traversing. This library sums up the authors 4-years experience when programming a commercial tool for graph traversing (which used a much more advanced algorithm) and coaching its users. -
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java-string-similarity
Implementation of various string similarity and distance algorithms
...This was published by Masek in 1980 ("A Faster Algorithm Computing String Edit Distances"). -
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MetaPA is a de Bruijn graph algorithm to obtain complete protein coding genes by assembling metagenomic and metatranscriptomic short reads. Jiemeng Liu*, Qichao Lian*, Yamao Chen, Ji Qi. (2019) Amino acid based de Bruijn graph algorithm for identifying complete coding genes from metagenomic and metatranscriptomic short reads. Nucleic Acids Research.
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Easy Machine Learning
Easy Machine Learning is a general-purpose dataflow-based system
...Our platform Easy Machine Learning presents a general-purpose dataflow-based system for easing the process of applying machine learning algorithms to real-world tasks. In the system, a learning task is formulated as a directed acyclic graph (DAG) in which each node represents an operation (e.g. a machine learning algorithm), and each edge represents the flow of the data from one node to its descendants.
