Search Results for "algorithms" - Page 4
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Showing 3542 open source projects for "algorithms"
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TIGRE
TIGRE: Tomographic Iterative GPU-based Reconstruction Toolbox
...Our aim is to provide a wide range of easy-to-use algorithms for the tomographic community "off the shelf". We would like to build a stronger bridge between algorithm developers and imaging researchers/clinicians by encouraging and supporting contributions from both sides to TIGRE. -
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vLLM
A high-throughput and memory-efficient inference and serving engine
vLLM is a fast and easy-to-use library for LLM inference and serving. High-throughput serving with various decoding algorithms, including parallel sampling, beam search, and more. -
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Ray
A unified framework for scalable computing
...Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best model and reduce training costs by using the latest optimization algorithms. Deploy your machine learning models at scale with Ray Serve, a Python-first and framework agnostic model serving framework. Scale reinforcement learning (RL) with RLlib, a framework-agnostic RL library that ships with 30+ cutting-edge RL algorithms including A3C, DQN, and PPO. Easily build out scalable, distributed systems in Python with simple and composable primitives in Ray Core. -
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CUDA Core Compute Libraries (CCCL)
CUDA Core Compute Libraries
...The goal of CCCL is to simplify CUDA development by offering reusable building blocks that enable developers to write efficient and scalable parallel code without starting from scratch. Thrust provides a high-level interface for parallel algorithms, while CUB delivers highly optimized primitives for device-level operations, and libcudacxx ensures compatibility with modern C++ standards. By unifying these components, CCCL reduces duplication and improves developer productivity while maintaining performance across different GPU architectures. -
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LightZero
[NeurIPS 2023 Spotlight] LightZero
...Developed by OpenDILab, LightZero focuses on providing a highly optimized and user-friendly platform for both academic research and industrial applications of MuZero and similar algorithms. -
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Reinforcement Learning Course Materials
Lecture notes, tutorial tasks including solutions
Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University. The source code for the entire course material is open and everyone is cordially invited to use it for self-learning (students) or to set up their own course (lecturers). -
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FATE
An industrial grade federated learning framework
...It implements secure computation protocols based on homomorphic encryption and multi-party computation (MPC). Supporting various federated learning scenarios, FATE now provides a host of federated learning algorithms, including logistic regression, tree-based algorithms, deep learning and transfer learning. FATE became open-source in February 2019. FATE TSC was established to lead FATE open-source community, with members from major domestic cloud computing and financial service enterprises. FedAI is a community that helps businesses and organizations build AI models effectively and collaboratively, by using data in accordance with user privacy protection, data security, data confidentiality and government regulations. -
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EASTL
EASTL, Electronic Arts Standard Template Library
EASTL stands for Electronic Arts Standard Template Library. It is a C++ template library of containers, algorithms, and iterators useful for runtime and tool development across multiple platforms. It is a fairly extensive and robust implementation of such a library and has an emphasis on high performance above all other considerations. If you are familiar with the C++ STL or have worked with other templated container/algorithm libraries, you probably don't need to read this. -
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PyMC3
Probabilistic programming in Python
...Variational inference saves computational cost by turning a problem of integration into one of optimization. PyMC3's variational API supports a number of cutting edge algorithms, as well as minibatch for scaling to large datasets. -
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The Hundred-Page Machine Learning Book
The Python code to reproduce illustrations from Machine Learning Book
...The book itself provides a concise overview of machine learning theory and practice, covering topics such as supervised learning, unsupervised learning, neural networks, and optimization algorithms. The repository complements these explanations by offering practical implementations that demonstrate how various algorithms behave when applied to data. Readers can explore the scripts to reproduce diagrams and observe how mathematical concepts translate into working code. -
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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 Scala, it shows the architecture of large-scale recommendation systems, including candidate sourcing, ranking, and heuristics. ... -
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XMRig
RandomX, KawPow, CryptoNight, AstroBWT and GhostRider unified miner
...The preferred way to configure the miner is the JSON config file as it is more flexible and human-friendly. The command-line interface does not cover all features, such as mining profiles for different algorithms. Important options can be changed during runtime without miner restart by editing the config file or executing API calls. -
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kcptun
A stable and secure tunnel based on KCP with N:M multiplexing and FEC
kcptun is a stable and secure tunnel based on KCP with N:M multiplexing and FEC. Available for ARM, MIPS, 386 and AMD64. kcptun is shipped with builtin packet encryption powered by various block encryption algorithms and works in Cipher Feedback Mode, for each packet to be sent, the encryption process will start from encrypting a nonce from the system entropy, so encryption to same plaintexts never leads to a same ciphertexts thereafter. kcptun made use of ReedSolomon-Codes to recover lost packets, which requires massive amount of computation, a low-end ARM device cannot satisfy kcptun well. ... -
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WindTerm
A professional cross-platform SSH/Sftp/Shell/Telnet/Serial terminal
...WindTerm is a partial open source project, and the source will be gradually opened. Open source code includes, but is not limited to, the classes that can be used independently, such as functional, algorithms, GUI widgets, etc., as well as functional libraries, such as networks, protocols, etc., as well as all types that require open source according to the license. SSH v2, Telnet, Raw TCP, Serial, Shell protocols were implemented. Supports SSH auto-execution when the session is authenticated. Integrated local file manager, supports the move to, copy to, copy from, remove, rename, make new file/directory and so on. ... -
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BindsNET
Simulation of spiking neural networks (SNNs) using PyTorch
A Python package used for simulating spiking neural networks (SNNs) on CPUs or GPUs using PyTorch Tensor functionality. BindsNET is a spiking neural network simulation library geared towards the development of biologically inspired algorithms for machine learning. This package is used as part of ongoing research on applying SNNs to machine learning (ML) and reinforcement learning (RL) problems in the Biologically Inspired Neural & Dynamical Systems (BINDS) lab. -
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JOSE JWT
Ultimate Javascript Object Signing and Encryption (JOSE)
Minimalistic zero-dependency library for generating, decoding, and encryption JSON Web Tokens. Supports full suite of JSON Web Algorithms and Json Web Keys. JSON parsing agnostic can plug any desired JSON processing library. Extensively tested for compatibility with jose.4.j, Nimbus-JOSE-JWT, and json-jwt libraries. JWE JSON Serialization cross-tested with JWCrypto. -
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Humanizer Skill
Claude Code skill that removes signs of AI-generated writing from text
Humanizer Skill is a utility library focused on transforming technical or machine-oriented text into expressions that are more natural, readable, and “human-friendly.” It provides a suite of algorithms that convert timestamps, identifiers, file sizes, code tokens, and structured data into phrases that resemble typical human phrasing rather than compact machine output. For example, date and time values can be expressed as relative terms (“two hours ago”), and file sizes can be shown in intuitive units instead of raw bytes. It also includes functions for transforming camelCase, snake_case, or PascalCase identifiers into spaced and capitalized representations suitable for user interfaces, reports, or documentation. ... -
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RL Games
RL implementations
rl_games is a high-performance reinforcement learning framework optimized for GPU-based training, particularly in environments like robotics and continuous control tasks. It supports advanced algorithms and is built with PyTorch. -
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Tequila
A High-Level Abstraction Framework for Quantum Algorithms
Tequila is an abstraction framework for (variational) quantum algorithms. It operates on abstract data structures allowing the formulation, combination, automatic differentiation and optimization of generalized objectives. Tequila can execute the underlying quantum expectation values on state-of-the-art simulators as well as on real quantum devices. -
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Open3D
A modern library for 3D data processing
Open3D is an open-source library that supports rapid development of software that deals with 3D data. The Open3D frontend exposes a set of carefully selected data structures and algorithms in both C++ and Python. The backend is highly optimized and is set up for parallelization. Open3D was developed from a clean slate with a small and carefully considered set of dependencies. It can be set up on different platforms and compiled from source with minimal effort. The code is clean, consistently styled, and maintained via a clear code review mechanism. ... -
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Alibi Explain
Algorithms for explaining machine learning models
Alibi is a Python library aimed at machine learning model inspection and interpretation. The focus of the library is to provide high-quality implementations of black-box, white-box, local and global explanation methods for classification and regression models. -
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Rubix ML
A high-level machine learning and deep learning library for PHP
...We provide tools for the entire machine learning life cycle from ETL to training, cross-validation, and production with over 40 supervised and unsupervised learning algorithms. In addition, we provide tutorials and other educational content to help you get started using ML in your projects. Our intuitive interface is quick to grasp while hiding alot of power and complexity. Write less code and iterate faster leaving the hard stuff to us. Rubix ML utilizes a versatile modular architecture that is defined by a few key abstractions and their types and interfaces. ... -
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Machine Learning Study
This repository is for helping those interested in machine learning
...The project compiles notebooks, explanatory documents, and practical code examples that illustrate common machine learning workflows. Topics covered include supervised learning algorithms, feature engineering, model training, and performance evaluation techniques. The repository is structured as a learning resource that guides readers through building machine learning models step by step. It often demonstrates how to implement algorithms using widely used libraries such as NumPy, pandas, scikit-learn, and TensorFlow. ... -
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LRSLibrary
Low-Rank and Sparse Tools for Background Modeling and Subtraction
LRSLibrary is a MATLAB library offering a broad collection of low-rank plus sparse decomposition algorithms, primarily aimed at background/foreground modeling from videos (background subtraction) and related computer vision tasks. Compatibility across MATLAB versions (tested in R2014–R2017) The library includes matrix and tensor methods (over 100 algorithms) and has been tested across MATLAB versions from R2014 onward. The algorithms can also be adapted to other computer vision or machine learning problems beyond video. ... -
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Frouros
Frouros is an open-source Python library for drift detection
Frouros is a Python library for drift detection in machine learning systems that provides a combination of classical and more recent algorithms for both concept and data drift detection.
