Showing 1396 open source projects for "genetic algorithm c"

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  • 1
    The Algorithms - C++ #

    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.
    Downloads: 1 This Week
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  • 2
    PyGAD

    PyGAD

    Source code of PyGAD, Python 3 library for building genetic algorithms

    PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine learning algorithms. It supports Keras and PyTorch. PyGAD supports optimizing both single-objective and multi-objective problems. PyGAD supports different types of crossover, mutation, and parent selection. PyGAD allows different types of problems to be optimized using the genetic algorithm by customizing the fitness function.
    Downloads: 2 This Week
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  • 3
    X's Recommendation Algorithm

    X's Recommendation Algorithm

    Source code for the X Recommendation Algorithm

    The Algorithm is Twitter’s open source release of the core ranking system that powers the platform’s home timeline. It provides transparency into how tweets are selected, prioritized, and surfaced to users, reflecting Twitter’s move toward openness in recommendation algorithms. The repository contains the recommendation pipeline, which incorporates signals such as engagement, relevance, and content features, and demonstrates how they combine to form ranked outputs. Written primarily in...
    Downloads: 1 This Week
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  • 4
    PlatEMO

    PlatEMO

    Evolutionary multi-objective optimization platform

    ...PlatEMO consists of a number of MATLAB functions without using any other libraries. Any machines able to run MATLAB can use PlatEMO regardless of the operating system. PlatEMO includes more than ninety existing popular MOEAs, including genetic algorithm, differential evolution, particle swarm optimization, memetic algorithm, estimation of distribution algorithm, and surrogate model-based algorithm. Most of them are representative algorithms published in top journals after 2010. Users can select various figures to be displayed, including the Pareto front of the result, the Pareto set of the result, the true Pareto front, and the evolutionary trajectories of any performance indicator values. ...
    Downloads: 18 This Week
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  • 5
    Anime4KCPP

    Anime4KCPP

    A high performance anime upscaler

    Anime4KCPP provides an optimized bloc97's Anime4K algorithm version 0.9, and it also provides its own CNN algorithm ACNet, it provides a variety of way to use, including preprocessing and real-time playback, it aims to be a high-performance tool to process both image and video. This project is for learning and the exploration task of the algorithm course in SWJTU. Anime4K is a simple high-quality anime upscale algorithm. Version 0.9 does not use any machine learning approaches and can be...
    Downloads: 39 This Week
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  • 6
    Zstandard

    Zstandard

    Zstandard - Fast real-time compression algorithm

    Zstandard is a fast compression algorithm, providing high compression ratios. It also offers a special mode for small data, called dictionary compression. The reference library offers a very wide range of speed / compression trade-off, and is backed by an extremely fast decoder (see benchmarks below). Zstandard library is provided as open source software using a BSD license. Its format is stable and published as IETF RFC 8478. The negative compression levels, specified with --fast=#, offer...
    Downloads: 89 This Week
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  • 7
    lsfg-vk

    lsfg-vk

    Lossless Scaling Frame Generation on Linux

    The lsfg-vk project is a Vulkan layer developed primarily by PancakeTAS that hooks into Vulkan-based applications to enhance rendering by generating additional frames using the Lossless Scaling frame generation algorithm originally associated with the Lossless Scaling project. Instead of relying on driver-specific or hardware-accelerated upscaling, this layer intercepts Vulkan API calls and injects frame interpolation on the fly, effectively producing smoother motion in supported games and...
    Downloads: 176 This Week
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  • 8
    pgapack, the parallel genetic algorithm library is a powerfull genetic algorithm library by D. Levine, Mathematics and Computer Science Division Argonne National Laboratory. The library is written in C. PGAPy wraps this library for use with Python.
    Downloads: 0 This Week
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  • 9
    Brotli

    Brotli

    Brotli compression format

    Version 1.0.9 contains a fix to "integer overflow" problem. This happens when "one-shot" decoding API is used (or input chunk for streaming API is not limited), input size (chunk size) is larger than 2GiB, and input contains uncompressed blocks. After the overflow happens, memcpy is invoked with a gigantic num value, that will likely cause the crash. Brotli is a generic-purpose lossless compression algorithm that compresses data using a combination of a modern variant of the LZ77 algorithm,...
    Downloads: 45 This Week
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  • 10
    FLUX.2-klein-4B

    FLUX.2-klein-4B

    Flux 2 image generation model pure C inference

    FLUX.2-klein-4B is a compact, high-performance C library implementation of the Flux optimization algorithm — an iterative approach for solving large-scale optimization problems common in scientific computing, machine learning, and numerical simulation. Written with a strong emphasis on simplicity, correctness, and performance, it abstracts the core logic of flux-based optimization into a minimal C API that can be embedded in broader applications without pulling in heavy dependencies. ...
    Downloads: 10 This Week
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  • 11
    nghttp2

    nghttp2

    HTTP/2 C Library and tools

    nghttp2 is an implementation of HTTP/2 and its header compression algorithm HPACK in C. The framing layer of HTTP/2 is implemented as a form of reusable C library. On top of that, we have implemented HTTP/2 client, server and proxy. We have also developed a load test and benchmarking tool for HTTP/2. We have participated in httpbis working group since HTTP/2 draft-04, which is the first implementation draft.
    Downloads: 5 This Week
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  • 12
    IGListKit

    IGListKit

    A data-driven UICollectionView framework for building fast lists

    IGListKit uses an algorithm adapted from a paper titled A technique for isolating differences between files by Paul Heckel. This algorithm uses a technique known as the longest common subsequence to find a minimal diff between collections in linear time O(n). It finds all inserts, deletes, updates, and moves between arrays of data. A working range is a range of section controllers who aren’t yet visible, but are near the screen. Section controllers are notified of their entrance and exit to...
    Downloads: 2 This Week
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  • 13
    xxHash

    xxHash

    Extremely fast non-cryptographic hash algorithm

    xxHash is an extremely fast non-cryptographic hash algorithm, working at RAM speed limit. It is proposed in four flavors (XXH32, XXH64, XXH3_64bits and XXH3_128bits). The latest variant, XXH3, offers improved performance across the board, especially on small data. It successfully completes the SMHasher test suite which evaluates collision, dispersion and randomness qualities of hash functions. Code is highly portable, and hashes are identical across all platforms (little / big endian)....
    Downloads: 3 This Week
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  • 14
    KACTL

    KACTL

    KTH algorithm competition template library

    KACTL (the KTH Algorithmic Contest Template Library) is an extensively curated and high-performance C++ algorithms library created by the competitive programming team at the Royal Institute of Technology (KTH) to serve as a trusted, battle-tested codebase for algorithmic contests, programming competitions, and general algorithm development. The repository aggregates dozens of concise implementations of essential data structures, numerical methods, graph algorithms, string processing tools, computational geometry routines, and optimization techniques, all designed with speed, correctness, and compactness in mind. ...
    Downloads: 1 This Week
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  • 15
    Smile

    Smile

    Statistical machine intelligence and learning engine

    Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster? Write applications quickly in Java, Scala, or any JVM...
    Downloads: 4 This Week
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  • 16
    Monero P2Pool

    Monero P2Pool

    Decentralized pool for Monero mining

    Decentralized pool for Monero mining. No central server that can be shutdown/blocked. P2Pool uses a separate blockchain to merge mine with Monero. Pool admin can't go rogue or be pressured to do an attack on the network because there is no pool admin.
    Downloads: 19 This Week
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  • 17
    Clustering.jl

    Clustering.jl

    A Julia package for data clustering

    Methods for data clustering and evaluation of clustering quality.
    Downloads: 4 This Week
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  • 18
    TSNE-CUDA

    TSNE-CUDA

    GPU Accelerated t-SNE for CUDA with Python bindings

    This repo is an optimized CUDA version of FIt-SNE algorithm with associated python modules. We find that our implementation of t-SNE can be up to 1200x faster than Sklearn, or up to 50x faster than Multicore-TSNE when used with the right GPU. You can install binaries with anaconda for CUDA version 10.1 and 10.2 using conda install tsnecuda -c conda-forge. Tsnecuda supports CUDA versions 9.0 and later through source installation, check out the wiki for up to date installation instructions. ...
    Downloads: 8 This Week
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  • 19
    yabai

    yabai

    A tiling window manager for macOS based on binary space partitioning

    yabai is a tiling window manager for macOS that extends the native windowing system with fully scriptable command-line control. It uses a binary space partitioning algorithm to auto-tile windows, supports extensive keyboard shortcut mapping (via skhd), and enhances productivity for power users.
    Downloads: 8 This Week
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  • 20
    The Operator Splitting QP Solver

    The Operator Splitting QP Solver

    The Operator Splitting QP Solver

    OSQP uses a specialized ADMM-based first-order method with custom sparse linear algebra routines that exploit structure in problem data. The algorithm is absolutely division-free after the setup and it requires no assumptions on problem data (the problem only needs to be convex). It just works. OSQP has an easy interface to generate customized embeddable C code with no memory manager required. OSQP supports many interfaces including C/C++, Fortran, Matlab, Python, R, Julia, Rust.
    Downloads: 2 This Week
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  • 21
    Vowpal Wabbit

    Vowpal Wabbit

    Machine learning system which pushes the frontier of machine learning

    Vowpal Wabbit is a machine learning system that pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning. There is a specific focus on reinforcement learning with several contextual bandit algorithms implemented and the online nature lending to the problem well. Vowpal Wabbit is a destination for implementing and maturing state-of-the-art algorithms with performance in mind. The input format for...
    Downloads: 2 This Week
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  • 22
    InterviewGuide

    InterviewGuide

    Repository that collects extensive computer science

    InterviewGuide is a widely-starred open-source repository that collects extensive computer science learning notes, interview preparation materials, and job search strategies aimed especially at students and early-career developers. It was created by a developer who documented his own journey from campus to tech industry, including detailed learning pathways for languages like C/C++, Go, JavaScript, and frameworks like Vue, as well as topics such as operating systems, networks, databases, and Redis. The repository contains curated algorithm and data structure explanations, collections of interview questions, high-frequency topics, and practical problem-solving guides to help users brush up on skills that are often tested in technical interviews.
    Downloads: 0 This Week
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  • 23
    firo

    firo

    The privacy-focused cryptocurrency

    Firo is a privacy-focused cryptocurrency implementing zero-knowledge proofs to enable anonymous transactions while maintaining decentralization and auditability. Formerly known as Zcoin, Firo pioneered several innovations in privacy tech including the Lelantus protocol, which enables unlinkable and untraceable transactions without the need for trusted setup. It combines cutting-edge cryptographic research with user-friendly features, making it accessible to both everyday users and privacy...
    Downloads: 8 This Week
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  • 24
    ArchiSteamFarm

    ArchiSteamFarm

    C# application with primary purpose of farming Steam cards

    ASF is a C# application with the primary purpose of farming Steam cards from multiple accounts simultaneously. Unlike Idle Master which works only for one account at a given time, while requiring Steam client running in the background and launching additional processes imitating "game-playing" status, ASF doesn't require any Steam client running in the background, doesn't launch any additional processes and is made to handle unlimited Steam accounts at once. In addition to that, it's meant...
    Downloads: 26 This Week
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  • 25
    SHAP

    SHAP

    A game theoretic approach to explain the output of ml models

    ...It connects optimal credit allocation with local explanations using the classic Shapley values from game theory and their related extensions. While SHAP can explain the output of any machine learning model, we have developed a high-speed exact algorithm for tree ensemble methods. Fast C++ implementations are supported for XGBoost, LightGBM, CatBoost, scikit-learn and pyspark tree models. To understand how a single feature effects the output of the model we can plot the SHAP value of that feature vs. the value of the feature for all the examples in a dataset. Since SHAP values represent a feature's responsibility for a change in the model output, the plot below represents the change in predicted house price as RM (the average number of rooms per house in an area) changes.
    Downloads: 7 This Week
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