Search Results for "java open source" - Page 14

Showing 460 open source projects for "java open source"

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  • 1
    ProbabilisticCircuits.jl

    ProbabilisticCircuits.jl

    Probabilistic Circuits from the Juice library

    This module provides a Julia implementation of Probabilistic Circuits (PCs), tools to learn structure and parameters of PCs from data, and tools to do tractable exact inference with them. Probabilistic Circuits provides a unifying framework for several family of tractable probabilistic models. PCs are represented as computational graphs that define a joint probability distribution as recursive mixtures (sum units) and factorizations (product units) of simpler distributions (input units)....
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  • 2
    NeuralOperators.jl

    NeuralOperators.jl

    DeepONets, Neural Operators, Physics-Informed Neural Ops in Julia

    Neural operator is a novel deep learning architecture. It learns an operator, which is a mapping between infinite-dimensional function spaces. It can be used to resolve partial differential equations (PDE). Instead of solving by finite element method, a PDE problem can be resolved by training a neural network to learn an operator mapping from infinite-dimensional space (u, t) to infinite-dimensional space f(u, t). Neural operator learns a continuous function between two continuous function...
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  • 3
    PowerSimulations.jl

    PowerSimulations.jl

    Julia for optimization simulation and modeling of PowerSystems

    PowerSimulations.jl is a Julia package for power system modeling and simulation of Power Systems operations. Provide a flexible modeling framework that can accommodate problems of different complexity and at different time scales. Streamline the construction of large-scale optimization problems to avoid repetition of work when adding/modifying model details. Exploit Julia's capabilities to improve computational performance of large-scale power system quasi-static simulations. The flexible...
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  • 4
    JLD.jl

    JLD.jl

    Saving and loading julia variables while preserving native types

    JLD, for which files conventionally have the extension .jld, is a widely used format for data storage with the Julia programming language. JLD is a specific "dialect" of HDF5, a cross-platform, multi-language data storage format most frequently used for scientific data. By comparison with "plain" HDF5, JLD files automatically add attributes and naming conventions to preserve type information for each object. For lossless storage of arbitrary Julia objects, the only other complete solution...
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  • 5
    CxxWrap

    CxxWrap

    Package to make C++ libraries available in Julia

    This package aims to provide a Boost. Python-like wrapping for C++ types and functions to Julia. The idea is to write the code for the Julia wrapper in C++, and then use a one-liner on the Julia side to make the wrapped C++ library available there. The mechanism behind this package is that functions and types are registered in C++ code that is compiled into a dynamic library. This dynamic library is then loaded into Julia, where the Julia part of this package uses the data provided through a...
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  • 6
    Measurements.jl

    Measurements.jl

    Error propagation calculator and library for physical measurements

    Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical integration. Physical measures are typically reported with an error, a quantification of the uncertainty of the accuracy of the measurement. Whenever you perform mathematical operations involving these quantities you have also to propagate the uncertainty, so that the resulting number will also have...
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  • 7
    PythonCall & JuliaCall

    PythonCall & JuliaCall

    Python and Julia in harmony

    Bringing Python® and Julia together in seamless harmony. Call Python code from Julia and Julia code from Python via a symmetric interface. Simple syntax, so the Python code looks like Python and the Julia code looks like Julia. Intuitive and flexible conversions between Julia and Python: anything can be converted, you are in control. Fast non-copying conversion of numeric arrays in either direction: modify Python arrays (e.g. bytes, array. array, numpy.ndarray) from Julia or Julia arrays...
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  • 8
    CUDA.jl

    CUDA.jl

    CUDA programming in Julia

    High-performance GPU programming in a high-level language. JuliaGPU is a GitHub organization created to unify the many packages for programming GPUs in Julia. With its high-level syntax and flexible compiler, Julia is well-positioned to productively program hardware accelerators like GPUs without sacrificing performance. The latest development version of CUDA.jl requires Julia 1.8 or higher. If you are using an older version of Julia, you need to use a previous version of CUDA.jl. This will...
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  • 9
    PackageCompiler

    PackageCompiler

    Compile your Julia Package

    Julia is, in general, a "just-barely-ahead-of-time" compiled language. When you call a function for the first time, Julia compiles it for precisely the types of arguments given. This can take some time. All subsequent calls within that same session use this fast compiled function, but if you restart Julia you lose all the compiled work. PackageCompiler allows you to do this work upfront — further ahead of time — and store the results for a lower latency startup. You can save loaded packages...
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  • 10
    FEniCS.jl

    FEniCS.jl

    A scientific machine learning (SciML) wrapper for the FEniCS

    FEniCS.jl is a wrapper for the FEniCS library for finite element discretizations of PDEs. This wrapper includes three parts. Installation and direct access to FEniCS via a Conda installation. Alternatively one may use their current FEniCS installation. A low-level development API and provides some functionality to make directly dealing with the library a little bit easier, but still requires knowledge of FEniCS itself. Interfaces have been provided for the main functions and their...
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  • 11
    Catalyst.jl

    Catalyst.jl

    Chemical reaction network and systems biology interface

    Catalyst.jl is a symbolic modeling package for analysis and high-performance simulation of chemical reaction networks. Catalyst defines symbolic ReactionSystems, which can be created programmatically or easily specified using Catalyst's domain-specific language (DSL). Leveraging ModelingToolkit and Symbolics.jl, Catalyst enables large-scale simulations through auto-vectorization and parallelism. Symbolic ReactionSystems can be used to generate ModelingToolkit-based models, allowing the easy...
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  • 12
    Pkg Julia

    Pkg Julia

    Package manager for the Julia programming language

    Unlike traditional package managers, which install and manage a single global set of packages, Pkg is designed around “environments”: independent sets of packages that can be local to an individual project or shared and selected by name. The exact set of packages and versions in an environment is captured in a manifest file which can be checked into a project repository and tracked in version control, significantly improving reproducibility of projects. If you’ve ever tried to run code you...
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  • 13
    Genie.jl

    Genie.jl

    The highly productive Julia web framework

    Genie Framework includes all you need to quickly build production-ready web applications with Julia. Develop Julia backends, create beautiful web UIs, build data applications and dashboards, integrate with databases and set up high-performance web services and APIs. Genie Builder is a free VSCode plugin for quickly building Julia apps without writing frontend code. Drag and drop UI components such as text, sliders, plots, and data tables onto a canvas, and connect them to the variables in...
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  • 14
    The NLopt module for Julia

    The NLopt module for Julia

    Package to call the NLopt nonlinear-optimization library from Julia

    This module provides a Julia-language interface to the free/open-source NLopt library for nonlinear optimization. NLopt provides a common interface for many different optimization algorithms.
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  • 15
    Dash for Julia

    Dash for Julia

    A Julia interface to the Dash ecosystem for creating analytic web apps

    Create beautiful, analytic applications in Julia. Built on top of Plotly.js, React and HTTP.jl, Dash ties modern UI elements like dropdowns, sliders, and graphs directly to your analytical Julia code.
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  • 16
    IterTools.jl

    IterTools.jl

    Common functional iterator patterns

    Common functional iterator patterns.
    Downloads: 0 This Week
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  • 17
    InteractiveErrors.jl

    InteractiveErrors.jl

    Interactive error messages for the Julia REPL

    Interactive error messages for the Julia REPL. Just start using your REPL normally. Once you hit an error you'll be presented with an interactive tree representing your stacktrace which you can explore. To turn interactive errors off and return to using normal stack traces call toggle(). Call toggle() again to turn it back on. Press up and down arrows to move through the stacktrace. Press space to fold or unfold the currently selected line. A + will appear on folded lines. Press enter once...
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  • 18
    Parsers.jl

    Parsers.jl

    fast parsing machinery for basic types in Julia

    A collection of type parsers and utilities for Julia. Installation: at the Julia REPL, import Pkg; Pkg.add("Parsers") Parsers is maintained collectively by the JuliaData collaborators. Responsiveness to pull requests and issues can vary, depending on the availability of key collaborators.
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  • 19
    PyCall.jl

    PyCall.jl

    Package to call Python functions from the Julia language

    Package to call Python functions from the Julia language. This package provides the ability to directly call and fully interoperate with Python from the Julia language. You can import arbitrary Python modules from Julia, call Python functions (with automatic conversion of types between Julia and Python), define Python classes from Julia methods, and share large data structures between Julia and Python without copying them.
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  • 20
    Bayesian Julia

    Bayesian Julia

    Bayesian Statistics using Julia and Turing

    Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used for making predictions about future events. Bayesian statistics is a departure from...
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  • 21
    LabPlot

    LabPlot

    Data Visualization and Analysis

    LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone.
    Downloads: 44 This Week
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  • 22
    Mousetrap.jl

    Mousetrap.jl

    Finally, a GUI Engine made for Julia

    Mousetrap is a GUI library designed for Julia. It fully wraps GTK4 (which is written in C), vastly simplifying its interface to improve ease of use without sacrificing flexibility. It aims to give developers of all skill levels the tools to start creating complex GUI applications with little time and effort while taking full advantage of Julia's idiosyncrasies.
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  • 23
    Metatheory.jl

    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...
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  • 24
    Bootstrap.jl

    Bootstrap.jl

    Statistical bootstrapping library for Julia

    Bootstrapping is a widely applicable technique for statistical estimation.
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  • 25
    EllipsisNotation.jl

    EllipsisNotation.jl

    Julia-based implementation of ellipsis array indexing notation

    Julia-based implementation of ellipsis array indexing notation. This implements the notation .. for indexing arrays. It's similar to Python, in that it means "all the columns before (or after)". Note: .. slurps dimensions greedily, meaning that the first occurrence of .. in an index expression creates as many slices as possible. Other instances of .. afterward are treated simply as slices. Usually, you should only use one instance of .. in an indexing expression to avoid possible confusion.
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