Search Results for "optimization" - Page 9
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Showing 283 open source projects for "optimization"
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cocolib / light field suite
CUDA library for continuous optimization and light field analysis
Library for continuous convex optimization in image analysis, together with a command line tool and Matlab interface. Implements several recent algorithms for inverse problems and image segmentation with total variation regularizers and vectorial multilabel transition costs. Also included is a suite for variational light field analysis, which ties into the HCI light field benchmark set and givens reference implementations for a number of our recently published algorithms. *** NOTE: documentation on the SourceForge page is outdated and not updated anymore, please visit http://cocolib.net *** -
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macOS VirtualBox VM Instructions
Instructions and script to help you create a VirtualBox VM
macOS VirtualBox VM is a repository that provides scripts and instructions to build a VirtualBox virtual machine running macOS (ranging across versions like Yosemite, El Capitan, Sierra, High Sierra, Mojave). The script automates preparation of the macOS installer ISO from the App Store application, configuration steps for VirtualBox, and setup guidance to get a working VM. This is valuable for developers who want to test, build, or deploy within macOS without relying on physical Mac... -
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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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NOMAD is a C++ code that implements the MADS algorithm (Mesh Adaptive Direct Search) for difficult blackbox optimization problems. Such problems occur when the functions to optimize are costly computer simulations with no derivatives.
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Douya Bean sprouts
A Material Design app for douban.com
The open source Material Design Douban client. Among all people who directly access Douban, the most common and consistent usage is around ratings, comments, discoveries, and discussions around movies, TV, books, records, and events (what we call "items"). We will use the ratings and comments that are synchronized with the website as a starting point and basis to reconstruct the discovery and discussion around personal interests on the mobile phone. Douban is never a single website, and the... -
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archer
An automated SQL operation platform based on inception
An automated SQL operation platform based on inception, supports functions such as work order, audit, scheduled task, email, OSC, etc., and can also configure MySQL query, slow query management, session management, etc. Initiate SQL launch, submit work orders, and automatically audit by inception. After the audit is passed, manual audit by the auditor is required. The rollback statement can be displayed in the work order, and it supports one-click submission of rollback work orders. Query... -
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jekyll-breadcrumbs
Creates breadcrumbs for Jekyll 3.x, includes SEO optimization
Smart and fast breadcrumbs for posts, pages and collections with SEO support and more. Works as Jekyll Hook with Jekyll 3.x. -
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JS-Data
Give your data the treatment it deserves
JSData is a framework-agnostic, datastore-agnostic ORM for Node.js and the Browser. Adapters allow JSData to connect to various data sources such as Firebase, MySql, RethinkDB, MongoDB, localStorage, Redis, a REST API, etc. With JSData you can re-use your data modeling code between environments, keep your data layer intact when transitioning between app frameworks, and work with a unified data API on the server and the client. JSData employs conventions for rapid development, but allows for... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Kickster
Worry-free deploying to GitHub Pages using Jekyll
Kickster provides a basic Jekyll project setup packed with web best practises and useful optimization tools increasing your overall project quality. Kickster ships with automated and worry-free deployment scripts for GitHub Pages. -
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APNG Assembler
Creates APNG animation from PNG/TGA image sequence.
Creates highly optimized Animated PNG files from PNG/TGA image sequences. CLI versions available for all major OSes. GUI versions for Windows and macOS. Also, APNG Disassembler can be found at http://sourceforge.net/projects/apngdis -
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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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node2vec
Learn continuous vector embeddings for nodes in a graph using biased R
The node2vec project provides an implementation of the node2vec algorithm, a scalable feature learning method for networks. The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction.... -
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jMetal is an object-oriented Java-based framework for solving multi-objective optimization problems with metaheuristics.
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Closure Compiler JS
Package for the JS version of closure-compiler for use via NPM
closure-compiler-js packages Google’s Closure Compiler so it runs under JavaScript (e.g., Node.js) instead of a JVM, making advanced JS optimization accessible in more build pipelines. You get the same aggressive whole-program optimizations—dead-code elimination, property renaming, inlining, and cross-module motion—delivered via a JS API and CLI. Because it’s the compiler you know, it also honors Closure type annotations and JSDoc, enabling type-aware rewrites that shrink bundles without breaking semantics. ... -
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Priority Estimation Tool (AHP)
PriEsT is a decision making tool for Analytic Hierarchy Process (AHP).
Priorty Estimation Tool (PriEsT) is a decision analysis tool. You can use it for ranking the options you have, or alternatively, you may use it for resource allocation (budgeting) problems. In PriEsT, you enter a list of available options and then define your criteria for prioritization. After defining criteria, PriEsT allows you to enter your judgements against each criterion, which are then used to calculate the final ranking (or weights). Please cite this if you find it... -
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Opt4J
Modular Java framework for meta-heuristic optimization
Opt4J is an open source Java-based framework for evolutionary computation. It contains a set of (multi-objective) optimization algorithms such as evolutionary algorithms (including SPEA2 and NSGA2), differential evolution, particle swarm optimization, and simulated annealing. The benchmarks that are included comprise ZDT, DTLZ, WFG, and the knapsack problem. The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary meta-heuristic optimization algorithms. ... -
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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... -
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webpack-howto
This is a cookbook of how to get things done with webpack
...It walks through loaders for CoffeeScript, JSX, ES6, CSS, LESS, and static images. It also explains production builds, source maps, bundle splitting, async loading, feature flags, shimming, testing, and optimization patterns. webpack-howto is best understood as a historical but still informative webpack learning reference for developers studying JavaScript build tooling. -
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NEW OPTIMIZATION TECHNOLOGY & PLANNING EXPERIMENT. Technology is designed for multidimensional optimization practical problems with continuous object functions. Technology higher efficiency than traditional optimization methods.
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iOS Tech Frontier
Tanslates high-quality iOS technology, open source libraries
...Instead of simple how-to recipes, the project collects detailed explanations, system internals analyses, and real-world insights into core subsystems like memory management (ARC), threading and Grand Central Dispatch, Objective-C/Swift runtime behavior, UIKit rendering pipelines, and effective use of concurrency. It also covers architectural and performance topics such as dynamic layout optimization, view lifecycle subtleties, Swift language pitfalls, and integration with low-level APIs such as Metal or CoreAnimation. By aggregating authoritative references, experiments, and code snippets, the guide helps developers reason through tradeoffs, debug subtle issues, and architect large-scale iOS systems. -
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ViennaCL
Linear algebra and solver library using CUDA, OpenCL, and OpenMP
ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects. -
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ngx_pagespeed
Automatic PageSpeed optimization module for Nginx
ngx_pagespeed speeds up your site and reduces page load time by automatically applying web performance best practices to pages and associated assets (CSS, JavaScript, images) without requiring you to modify your existing content or workflow. Apache PageSpeed is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure,... -
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RStan
RStan, the R interface to Stan
...Key inference approaches include full Bayesian inference via Hamiltonian Monte Carlo (specifically the No-U-Turn Sampler, NUTS), approximate Bayesian inference via variational methods, and optimization (penalized likelihood). RStan integrates with Stan’s automatic differentiation library, provides diagnostics, model comparison, posterior predictive checks, etc. It is used in research, applied statistics, and modelling workflows where flexibility and rigor in Bayesian methods are required.