Search Results for "optimization" - Page 2
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55 projects for "optimization" with 2 filters applied:
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ClashN
A clash client for Windows, support Mihomo
...System-wide proxy control, including PAC and TUN/TAP options, helps route applications that don’t natively support proxies. Logs, traffic charts, and connection inspectors make troubleshooting and optimization straightforward. For power users, granular profile editing and hot-reloading reduce the friction of iterating on configurations. -
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Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
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C++ Library of Abstract Algebra concepts and arithmetic algorithms defined in terms of these concepts, using Instigate Generic Programming Methodology. Based on this library we plan to develop Linear Algebra and Optimization concepts and algorithms.
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hummingbird
The most sensible component system for Tailwind.
Hummingbird is a component system for Tailwind developers who care about architectural discipline. It ensures global design control with local utility flexibility. Hummingbird is a lightweight, framework-agnostic tool that integrates seamlessly with modern stacks and helps build scalable, maintainable web applications without extra weight. -
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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. ... -
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learn2learn
A PyTorch Library for Meta-learning Research
...It provides reusable components and meta-learning algorithms, making it easier to build, train, and evaluate models that can quickly adapt to new tasks with minimal data. Learn2Learn is widely used in research for tasks such as few-shot classification, reinforcement learning, and optimization. -
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es-utils
ElasticSearch Utilities
es-utils is a collection of command-line utilities designed to simplify the monitoring and management of Elasticsearch clusters. It provides tools for searching, monitoring, and maintaining Elasticsearch indices, making cluster administration more efficient. -
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OptimTraj
A trajectory optimization library for Matlab
OptimTraj is a MATLAB toolbox for solving trajectory optimization problems. It supports direct collocation, shooting methods, and pseudospectral methods for finding optimal control inputs and system trajectories. It is useful for robotics, aerospace, biomechanics, and any domain requiring time-optimal or energy-optimal motion planning. -
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Java Best Practices
Best practices in Coding, Designing and Architecting Java Applications
...It provides guidelines and examples that demonstrate how to write clean, efficient, and scalable code following industry standards. The project covers topics such as naming conventions, exception handling, performance optimization, and design principles. It helps developers transition from basic coding knowledge to professional-level practices. The repository emphasizes consistency and clarity in code structure, making it easier to collaborate in team environments. It also introduces patterns that reduce technical debt and improve long-term maintainability. ... -
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Angular Performance Checklist
Cheatsheet for developing lightning fast progressive Angular apps
...It outlines actionable recommendations — from bundling and minification, tree-shaking, lazy loading, ahead-of-time (AoT) compilation, resource prefetching, caching and compression, to runtime strategies like change-detection optimization (OnPush, detaching change detectors), minimizing DOM operations, optimizing templates, using pure pipes, minimizing watchers, and more. The checklist is designed to be framework-agnostic in many parts, but especially valuable for Angular developers wanting to build responsive, fast-loading, efficient single-page applications. -
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Julia.jl
Curated decibans of Julia programming language
Julia.jl is a curated collection of knowledge resources for the Julia programming language, designed to support high-performance numerical analysis and computational science. The repository aggregates diverse content across domains such as mathematics, physics, data science, optimization, machine learning, and supercomputing. It functions as a structured index, helping developers, researchers, and learners easily find materials to deepen their understanding of Julia’s ecosystem. The project emphasizes community contributions, encouraging users to expand and refine the resource pool. With a wide range of topic-focused documents, it provides both academic and practical references for applied research and development. ... -
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Game-Programmer-Study-Notes
A collection of reading notes from my career as a game programmer
The Game-Programmer-Study-Notes project is a comprehensive collection of study materials aimed at aspiring and professional game developers. It compiles notes, tutorials, and references covering a wide range of topics such as graphics programming, game engine architecture, mathematics, and optimization techniques. The repository is structured to guide learners through fundamental and advanced concepts, making it suitable for both beginners and experienced programmers. It includes insights from industry practices as well as academic knowledge, bridging the gap between theory and real-world application. The content is often supplemented with diagrams, examples, and explanations that clarify complex topics. ... -
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libRSF
A robust sensor fusion library for online localization
...The general idea of factor graphs is to describe the state estimation problem as a graph of nodes (the state variables) that are connected by factors (measurements). The resulting graph optimization problem can be solved by applying non-linear least squares optimization. -
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Zopfli
Zopfli Compression Algorithm is a compression library
...A companion utility, zopflipng, targets PNGs by trying alternate filter strategies and recompressing IDAT chunks, often achieving additional savings without changing image quality. The codebase includes both a reusable library and ready-to-use CLI tools for bulk optimization in build pipelines. It is frequently used offline—e.g., as a final step in release builds—because decode speed remains normal while files get smaller. -
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Browser diet
The definitive front-end performance guide
...The project was built as a static site powered by DocPad, with content written in Markdown and translated into multiple languages, making it accessible to a global audience. Its tone is intentionally playful (with a “diet” metaphor for trimming page weight) to make performance optimization less intimidating and more approachable. The repository provides the full source of the site, including styles, content, and build pipeline so others can run it locally or fork it to create customized guides. Even though it is not a tool or library, browser-diet has been influential as an educational resource that demystifies front-end performance. -
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TF Quant Finance
High-performance TensorFlow library for quantitative finance
TF Quant Finance is a high-performance library of quantitative finance components built on TensorFlow, aimed at research and production workloads. It implements pricing engines, risk measures, stochastic models, optimizers, and random number generators that are differentiable and vectorized for accelerators. Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. The... -
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pytorch-examples
Simple examples to introduce PyTorch
The pytorch-examples project is a collection of concise and practical examples demonstrating how to use PyTorch for machine learning and deep learning tasks. It focuses on clarity and minimalism, providing small, self-contained scripts that illustrate key concepts such as neural network training, optimization, and data handling. The examples cover a range of topics including supervised learning, generative models, and reinforcement learning, making it a valuable resource for both beginners and experienced practitioners. By emphasizing readable code, the repository helps users understand how PyTorch’s imperative programming style enables flexible model development. ... -
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Enlive
Selector-based templating and transformation system for Clojure
...It allows selecting, transforming, and generating HTML fragments using CSS selectors, and supports server-side template composition, dynamic pages, and content rewriting. By default selector-transformation pairs are run sequentially. When you know that several transformations are independent, you can now specify (as an optimization) to process them in lockstep. Note that this doesn't work with fragments selectors. Transformations are now slightly restricted in their return values: a node or a collection of nodes (instead of freely nested collections of nodes). -
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Functional, Data Science Intro To Python
[tutorial]A functional, Data Science focused introduction to Python
...The assumption is a someone with zero experience in programming can follow this tutorial and learn Python with the smallest amount of information possible. The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing. -
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QuoJS
Micro #JavaScript Library for Mobile Devices
QuoJS is a lightweight JavaScript library aimed at building mobile-first web interfaces with a focus on touch interactions and simple DOM utilities. It provides a compact, jQuery-like API for element selection, traversal, and manipulation, but trims the surface area to keep payloads small for mobile browsers. A core feature set centers on high-level touch gestures—such as tap, double-tap, swipe, pinch, and long-tap—abstracting away platform quirks so developers can attach handlers... -
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GradlePluginDevelop
Gradle execution process
...It contains sample plugin code, project structure, examples of applying plugin logic, extension configuration, and build integration for Gradle plugin development. Gradle execution process, what is DSL, domain-specific language, common usage of Gradle, usage of Gradle advanced plug-ins, Gradle optimization for Android, using Javassist to the next floor, and problems encountered in Gradle development. Demonstration of plugin application in other modules. Plugin configuration and metadata. -
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Compare GAN
Compare GAN code
compare_gan is a research codebase that standardizes how Generative Adversarial Networks are trained and evaluated so results are comparable across papers and datasets. It offers reference implementations for popular GAN architectures and losses, plus a consistent training harness to remove confounding differences in optimization or preprocessing. The library’s evaluation suite includes widely used metrics and diagnostics that quantify sample quality, diversity, and mode coverage. With configuration-driven experiments, you can sweep hyperparameters, run ablations, and log results at scale. The goal is to turn GAN experimentation into a disciplined, repeatable process rather than a patchwork of scripts. ... -
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Solid Python
A comprehensive gradient-free optimization framework written in Python
Solid is a Python framework for gradient-free optimization. It contains basic versions of many of the most common optimization algorithms that do not require the calculation of gradients, and allows for very rapid development using them. -
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fast-neural-style
Feedforward style transfer
...It uses convolutional neural networks to apply artistic styles to images, enabling users to transform photos into stylized outputs inspired by famous artworks. Unlike earlier approaches that required expensive optimization per image, this project leverages feed-forward networks to achieve fast inference, making style transfer practical for real-world applications. The repository includes training scripts, pre-trained models, and examples demonstrating how to apply styles efficiently. It also provides insights into the underlying techniques used in neural style transfer, making it both a practical tool and a learning resource. ... -
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CRFasRNN
Semantic image segmentation method described in the ICCV 2015 paper
CRF-RNN is a deep neural architecture that integrates fully connected Conditional Random Fields (CRFs) with Convolutional Neural Networks (CNNs) by reformulating mean-field CRF inference as a Recurrent Neural Network. This fusion enables end-to-end training via backpropagation for semantic image segmentation tasks, eliminating the need for separate, offline post-processing steps. Our work allows computers to recognize objects in images, what is distinctive about our work is that we also...
