Math.NET Numerics is the numerical foundation of the Math.NET project, aiming to provide methods and algorithms for numerical computations in science, engineering and every day use. Supports .NET 5.0 or higher, .NET Standard 2.0 and .NET Framework 4.6.1 or higher, on Windows, Linux and Mac.
Contains a matrix extension library, along with a suite of numerical matrix decomposition methods, numerical optimization algorithms for constrained and unconstrained problems, special functions and other tools for scientific applications. This package is part of the Accord.NET Framework.
F# Modules for Math.NET Numerics, the numerical foundation of the Math.NET project, aiming to provide methods and algorithms for numerical computations in science, engineering and every day use. Supports .NET 5.0 or higher, .NET Standard 2.0 and .NET Framework 4.6.1 or higher, on Windows, Linux and...
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Math.NET Numerics is the numerical foundation of the Math.NET project, aiming to provide methods and algorithms for numerical computations in science, engineering and every day use. Supports .NET 5.0 or higher, .NET Standard 2.0 and .NET Framework 4.6.1 or higher, on Windows, Linux and Mac. This...
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Math.NET Symbolics is a basic open source computer algebra library for .Net and Mono. Written in F# but works well in C# as well. Supports .Net Framework 4.5 or higher and .Net Standard 2.0 or higher, on Windows, Linux and Mac.
A small library for performing matrix math, linear algebra - now including sparse matrix solve. Most functions are static and use simple arrays (e.g double[,]) making it easy to use in other projects.
Lightweight optimizer of System.Linq.Expression expressions. Just basic boolean algebra and reductions, constant and tuple/anonymous type eliminations. For side-effect free Expressions. No compilation-subjective optimizations.
The GPU-accelerated version of package CenterSpace.NMath. With a few minor exceptions, such as optional GPU configuration settings, the API is identical between CenterSpace.NMath.Premium and CenterSpace.NMath. If using at least .NET Framework 4.6.1 or .NET Core 2.0, we recommend using one of our...
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Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares...
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The Extreme Optimization Numerical Libraries for .NET are a set of libraries for numerical computing and data analysis.
This is the main package that contains all the core functionality.
For optimal performance, we strongly recommend also referencing one of the native packages based on Intel's...
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Bright Wire is an open source machine learning library. Includes neural networks (feed forward, convolutional and recurrent), naive bayes, linear regression, decision trees, logistic regression, k-means clustering and dimensionality reduction.
Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares...
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C# bindings for NumPy on Win64 - a fundamental library for scientific computing, machine learning and AI. Does require Python 3.8 with NumPy 1.16 installed!
FsAlg is a linear algebra library that supports generic types. It is implemented in the F# language.
The library provides generic Vector and Matrix types that support most of the commonly used linear algebra operations, including matrixâ€“vector operations, matrix inverse, determinants, eigenvalues,...
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A simple cross platform .NET API for Intel MKL.
Reference the MKL.NET package and required runtime packages and use the static MKL functions. The correct native libraries will be included and loaded at runtime.
Exposing functions from MKL keeping the syntax as close to the c developer reference as...
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