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AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero
Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++)... -
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Trixi.jl
Trixi.jl: Adaptive high-order numerical simulations of hyperbolic PDEs
Trixi.jl is a numerical simulation framework for hyperbolic conservation laws written in Julia. A key objective for the framework is to be useful to both scientists and students. Therefore, next to having an extensible design with a fast implementation, Trixi.jl is focused on being easy to use for new or inexperienced users, including the installation and postprocessing procedures. -
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Revise.jl
Automatically update function definitions in a running Julia session
Revise.jl is a Julia package that automatically updates functions, types, and modules in a running Julia session when their source code changes. It significantly improves the development workflow by removing the need to restart the REPL or re-include files after edits. Revise is ideal for iterative coding, package development, and interactive exploration, enabling a fast and fluid programming experience. -
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QML
Build Qt6 QML interfaces for Julia programs
This package provides an interface to Qt6 QML (and to Qt5 for older versions). It uses the CxxWrap package to expose C++ classes. Current functionality allows interaction between QML and Julia using Observables, JuliaItemModels and function calling. There is also a generic Julia display, as well as specialized integration for image drawing, GR plots and Makie. -
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HTTP.jl
HTTP for Julia
HTTP.jl is a pure Julia implementation of the HTTP protocol, providing tools for building HTTP clients and servers. It enables users to send requests, handle responses, and construct REST APIs or web services entirely in Julia. HTTP.jl supports TLS, cookies, headers, streaming, and middleware, making it suitable for both simple scripting and full-scale web service development. -
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ModelingToolkitStandardLibrary.jl
A standard library of components to model the world and beyond
The ModelingToolkit Standard Library is a standard library of components to model the world and beyond. -
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The Julia Programming Language
High-level, high-performance dynamic language for technical computing
Julia is a fast, open source high-performance dynamic language for technical computing. It can be used for data visualization and plotting, deep learning, machine learning, scientific computing, parallel computing and so much more. Having a high level syntax, Julia is easy to use for programmers of every level and background. Julia has more than 2,800 community-registered packages including various mathematical libraries, data manipulation tools, and packages for general purpose... -
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MLJBase.jl
Core functionality for the MLJ machine learning framework
Repository for developers that provides core functionality for the MLJ machine learning framework. MLJ is a Julia framework for combining and tuning machine learning models. This repository provides core functionality for MLJ. -
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IntervalArithmetic.jl
Library for validated numerics using interval arithmetic
IntervalArithmetic.jl is a Julia package for validated numerics in Julia. All calculations are carried out using interval arithmetic where quantities are treated as intervals. The final result is a rigorous enclosure of the true value. We are working towards having the IntervalArithmetic library be conformant with the IEEE 1788-2015 Standard for Interval Arithmetic. To do so, we have incorporated tests from the ITF1788 test suite. -
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PromptingTools.jl
Streamline your life using PromptingTools.jl
PromptingTools.jl is a Julia-based toolkit designed to simplify prompt engineering and unify interactions with multiple large language model providers through a consistent interface. It focuses on reducing the complexity of prompt creation by introducing templating systems, macros, and reusable functions that standardize how prompts are constructed and executed. The library provides a family of ai* functions that handle tasks such as generation, embeddings, classification, and data... -
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General
The official registry of general Julia packages
General is the default package registry for the Julia programming language, providing the foundation for Julia’s package manager, Pkg.jl. It stores essential information about packages, including versions, dependencies, and compatibility constraints, and serves as the central hub for the Julia package ecosystem. The registry is open to all and makes it easy for developers and researchers to access, install, and share packages across a wide range of domains. New packages and updates are added... -
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ConcurrentSim.jl
Discrete event process oriented simulation framework written in Julia
A discrete event process-oriented simulation framework written in Julia inspired by the Python library SimPy. One of the longest-lived Julia packages (originally under the name SimJulia). -
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BenchmarkTools.jl
A benchmarking framework for the Julia language
BenchmarkTools makes performance tracking of Julia code easy by supplying a framework for writing and running groups of benchmarks as well as comparing benchmark results. This package is used to write and run the benchmarks found in BaseBenchmarks.jl. The CI infrastructure for automated performance testing of the Julia language is not in this package but can be found in Nanosoldier.jl. Our story begins with two packages, "Benchmarks" and "BenchmarkTrackers". The Benchmarks package... -
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StructuralEquationModels.jl
A fast and flexible Structural Equation Modelling Framework
This is a package for Structural Equation Modeling in development. It is written for extensibility, that is, you can easily define your own objective functions and other parts of the model. At the same time, it is (very) fast. We provide fast objective functions, gradients, and for some cases hessians as well as approximations thereof. As a user, you can easily define custom loss functions. For those, you can decide to provide analytical gradients or use finite difference approximation /... -
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PkgTemplates.jl
Create new Julia packages, the easy way
PkgTemplates.jl is a Julia package that automates the creation of new Julia packages by generating a project scaffold with common best practices. It helps users quickly set up reproducible project structures with Git integration, CI configuration, testing frameworks, documentation, and more. By using customizable templates, PkgTemplates streamlines package development and enforces consistency across Julia projects. -
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GDAL.jl
Thin Julia wrapper for GDAL - Geospatial Data Abstraction Library
Julia wrapper for GDAL - Geospatial Data Abstraction Library. This package is a binding to the C API of GDAL/OGR. It provides only a C style usage, where resources must be closed manually, and datasets are pointers. Other packages can build on top of this to provide a more Julian user experience. See for example ArchGDAL.jl. Most users will want to use ArchGDAL.jl instead of using GDAL.jl directly. -
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Interpolations.jl
Fast, continuous interpolation of discrete datasets in Julia
This package implements a variety of interpolation schemes for the Julia language. It has the goals of ease of use, broad algorithmic support, and exceptional performance. Currently, this package supports B-splines and irregular grids. The API has been designed with the intent to support more options. Initial support for Lanczos interpolation was recently added. Pull requests are more than welcome! It should be noted that the API may continue to evolve over time. -
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DynamicalSystems.jl
Award winning software library for nonlinear dynamics timeseries
DynamicalSystems.jl is an award-winning Julia software library for nonlinear dynamics and nonlinear time series analysis. To install DynamicalSystems.jl, run import Pkg; Pkg.add("DynamicalSystems"). To learn how to use it and see its contents visit the documentation, which you can either find online or build locally by running the docs/make.jl file. DynamicalSystems.jl is part of JuliaDynamics, an organization dedicated to creating high-quality scientific software. All implemented algorithms... -
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GeoStats.jl
An extensible framework for geospatial data science
GeoStats.jl is a Julia framework for geospatial data science and geostatistical modeling. It’s fully implemented in Julia and designed to provide an extensible, high-performance stack that handles spatial domains, interpolation, simulation, learning, and visualization. The package is modular: it breaks out geometry, spatial domains, transforms, variograms, covariance models, and modeling into subpackages (e.g., GeoStatsBase, GeoStatsModels, GeoStatsTransforms). Users can represent... -
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GLM.jl
Generalized linear models in Julia
GLM.jl is a Julia package for fitting linear and generalized linear models (GLMs) with a syntax and functionality familiar to users of R or other statistical environments. It is part of the JuliaStats ecosystem and is tightly integrated with StatsModels.jl for formula handling, and Distributions.jl for specifying error families. The package supports modeling through both formula-based (e.g. @formula) and matrix-based interfaces, allowing both high-level convenience and low-level control.... -
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FFTW.jl
Julia bindings to the FFTW library for fast Fourier transforms
This package provides Julia bindings to the FFTW library for fast Fourier transforms (FFTs), as well as functionality useful for signal processing. These functions were formerly a part of Base Julia. Users with a build of Julia based on Intel's Math Kernel Library (MKL) can use MKL for FFTs by setting a preference in their top-level project by either using the FFTW.set_provider!() method, or by directly setting the preference using Preferences.jl. Note that this choice will be recorded for... -
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Evolutionary.jl
Evolutionary & genetic algorithms for Julia
A Julia package for evolutionary & genetic algorithms. The package can be installed with the Julia package manager. -
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Gen.jl
A general-purpose probabilistic programming system
An open-source stack for generative modeling and probabilistic inference. Gen’s inference library gives users building blocks for writing efficient probabilistic inference algorithms that are tailored to their models, while automating the tricky math and the low-level implementation details. Gen helps users write hybrid algorithms that combine neural networks, variational inference, sequential Monte Carlo samplers, and Markov chain Monte Carlo. Gen features an easy-to-use modeling language... -
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MLJ
A Julia machine learning framework
MLJ (Machine Learning in Julia) is a toolbox written in Julia providing a common interface and meta-algorithms for selecting, tuning, evaluating, composing and comparing about 200 machine learning models written in Julia and other languages. The functionality of MLJ is distributed over several repositories illustrated in the dependency chart below. These repositories live at the JuliaAI umbrella organization. -
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Memento.jl
A flexible logging library for Julia
Memento is a flexible hierarchical logging library for Julia.