Showing 5 open source projects for "library"

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    LazySets.jl

    LazySets.jl

    Scalable Symbolic-Numeric Set Computations

    ...This library implements types to construct set formulas and methods to efficiently and accurately approximate the projection in low dimensions.
    Downloads: 0 This Week
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  • 2
    Integrals.jl

    Integrals.jl

    A common interface for quadrature and numerical integration

    ...By using Integrals.jl, you get a single predictable interface where many of the arguments are standardized throughout the various integrator libraries. This can be useful for benchmarking or for library implementations since libraries that internally use a quadrature can easily accept an integration method as an argument.
    Downloads: 0 This Week
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  • 3
    ITensors.jl

    ITensors.jl

    A Julia library for efficient tensor computations and tensor network

    ITensors.jl is a high-performance Julia library for tensor network calculations, primarily used in quantum physics and computational science. It enables efficient manipulation of large, structured tensors with named indices and provides an intuitive interface for implementing algorithms like DMRG (Density Matrix Renormalization Group), TEBD (Time-Evolving Block Decimation), and more.
    Downloads: 0 This Week
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  • 4
    Symbolics.jl

    Symbolics.jl

    Symbolic programming for the next generation of numerical software

    Symbolics.jl is a high-performance symbolic computation library for the Julia programming language. It enables users to define, manipulate, and analyze mathematical expressions symbolically, with strong support for symbolic differentiation, simplification, equation solving, and code generation. Designed for use in scientific computing, machine learning, and engineering, Symbolics.jl integrates smoothly with Julia’s numerical ecosystem, allowing symbolic expressions to be compiled and optimized for high-speed evaluation.
    Downloads: 0 This Week
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  • 5
    MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
    Downloads: 0 This Week
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