Showing 13 open source projects for "mathematical"

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  • 1
    Nemo.jl

    Nemo.jl

    Julia bindings for various mathematical libraries (including flint2)

    Nemo is a computer algebra package for the Julia programming language. It aims to cover commutative algebra, number theory and group theory. Julia bindings for various mathematical libraries (including flint2)
    Downloads: 0 This Week
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  • 2
    BasicBSpline.jl

    BasicBSpline.jl

    Basic (mathematical) operations for B-spline functions

    Basic (mathematical) operations for B-spline functions and related things with Julia.
    Downloads: 0 This Week
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  • 3
    Measurements.jl

    Measurements.jl

    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 an attached error to quantify the confidence about its accuracy. Measurements.jl relieves you from the hassle of propagating uncertainties coming from physical measurements, when performing mathematical operations involving them. ...
    Downloads: 0 This Week
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  • 4
    SciMLBase.jl

    SciMLBase.jl

    The Base interface of the SciML ecosystem

    SciMLBase.jl is the core interface definition of the SciML ecosystem. It is a low-dependency library made to be depended on by the downstream libraries to supply the common interface and allow for the interexchange of mathematical problems. The SciML common interface ties together the numerical solvers of the Julia package ecosystem into a single unified interface. It is designed for maximal efficiency and parallelism, while incorporating essential features for large-scale scientific machine learning such as differentiability, composability, and sparsity.
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  • 5
    AppleAccelerate.jl

    AppleAccelerate.jl

    Julia interface to the macOS Accelerate framework

    ...At the moment, this package provides access to Accelerate BLAS and LAPACK using the libblastrampoline framework, an interface to the array-oriented functions, which provide a vectorized form for many common mathematical functions. The performance is significantly better than using standard libm functions in some cases, though there does appear to be some reduced accuracy.
    Downloads: 3 This Week
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  • 6
    The Julia Programming Language

    The Julia Programming Language

    High-level, high-performance dynamic language for technical computing

    ...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 computing. Libraries from Python, R, C/Fortran, C++, and Java can also be used.
    Downloads: 5 This Week
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  • 7
    InfiniteOpt.jl

    InfiniteOpt.jl

    An intuitive modeling interface for infinite-dimensional optimization

    A JuMP extension for expressing and solving infinite-dimensional optimization problems. InfiniteOpt.jl provides a general mathematical abstraction to express and solve infinite-dimensional optimization problems (i.e., problems with decision functions). Such problems stem from areas such as space-time programming and stochastic programming. InfiniteOpt is meant to facilitate intuitive model definition, automatic transcription into solvable models, permit a wide range of user-defined extensions/behavior, and more.
    Downloads: 0 This Week
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  • 8
    Surrogates.jl

    Surrogates.jl

    Surrogate modeling and optimization for scientific machine learning

    A surrogate model is an approximation method that mimics the behavior of a computationally expensive simulation. In more mathematical terms: suppose we are attempting to optimize a function f(p), but each calculation of f is very expensive. It may be the case we need to solve a PDE for each point or use advanced numerical linear algebra machinery, which is usually costly. The idea is then to develop a surrogate model g which approximates f by training on previous data collected from evaluations of f.
    Downloads: 0 This Week
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  • 9
    Unitful.jl

    Unitful.jl

    Physical quantities with arbitrary units

    ...We also want to minimize or in some cases eliminate the run-time penalty of units. There should be facilities for dimensional analysis. All of this should integrate easily with the usual mathematical operations and collections that are found in Julia base.
    Downloads: 0 This Week
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  • 10
    BinaryBuilder

    BinaryBuilder

    Binary Dependency Builder for Julia

    ...Package installation is merely downloading, verifying package integrity and extracting that tarball on the user's computer. No more compiling on user's machines. No more struggling with system package managers. No more needing sudo access to install that little mathematical optimization library.
    Downloads: 0 This Week
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  • 11
    Convex.jl

    Convex.jl

    A Julia package for disciplined convex programming

    Convex.jl is a Julia package for Disciplined Convex Programming (DCP). Convex.jl makes it easy to describe optimization problems in a natural, mathematical syntax, and to solve those problems using a variety of different (commercial and open-source) solvers. Convex.jl works by transforming the problem—which possibly has nonsmooth, nonlinear constructions like the nuclear norm, the log determinant, and so forth—into a linear optimization problem subject to conic constraints. This reformulation often involves adding auxiliary variables and is called an "extended formulation", since the original problem has been extended with additional variables. ...
    Downloads: 0 This Week
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  • 12
    Optimization.jl

    Optimization.jl

    Mathematical Optimization in Julia

    Optimization.jl provides the easiest way to create an optimization problem and solve it. It enables rapid prototyping and experimentation with minimal syntax overhead by providing a uniform interface to >25 optimization libraries, hence 100+ optimization solvers encompassing almost all classes of optimization algorithms such as global, mixed-integer, non-convex, second-order local, constrained, etc. It allows you to choose an Automatic Differentiation (AD) backend by simply passing an...
    Downloads: 0 This Week
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  • 13
    Gridap.jl

    Gridap.jl

    Grid-based approximation of partial differential equations in Julia

    Gridap provides a set of tools for the grid-based approximation of partial differential equations (PDEs) written in the Julia programming language. The library currently supports linear and nonlinear PDE systems for scalar and vector fields, single and multi-field problems, conforming and nonconforming finite element (FE) discretizations, on structured and unstructured meshes of simplices and n-cubes. It also provides methods for time integration. Gridap is extensible and modular. One can...
    Downloads: 0 This Week
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