10 packages tagged with “SVD”
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.
C# bindings for NumPy - a fundamental library for scientific computing, machine learning and AI. Does not require a local Python installation!
C# bindings for NumPy on Win64 - a fundamental library for scientific computing, machine learning and AI. Does require Python 3.7 with NumPy 1.16 installed!
C# bindings for NumPy on Linux - a fundamental library for scientific computing, machine learning and AI. Does require Python 3.8 with NumPy 1.16 installed!
C# bindings for NumPy on OSX - a fundamental library for scientific computing, machine learning and AI. Does require Python 3.8 with NumPy 1.16 installed!
MathCore Library - Linear Algebra
CuPy.NET is a wrapper library for CuPy in Python.
==================================== Bluebit .NET Matrix Library - 64 bit ==================================== This is a free version of .NET Matrix Library (NML™) which will allow matrix sizes up to 1000 x 1000. The Bluebit .NET Matrix Library (NML™) provides classes for object-oriented linear algebra in the .NET platform. It can be used to solve systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalues and eigenvectors problems, and singular value problems. Also provided are the associated matrix factorizations such as Eigen, LQ, LU, Cholesky, QR, SVD. .NET Matrix Library (NML™) also supports sparse matrices and advanced methods for solving large sparse systems of linear equations. The above functionality is present for both real and complex matrices. Two analogous sets of classes are provided for real and complex matrices, vectors and factorizations. While exposing an easy to use and powerful interface, the Bluebit .NET Matrix Library does not sacrifice any performance. Highly optimized BLAS and the standard LAPACK routines are used within the library and provide fast execution and accurate calculations. The Bluebit .NET Matrix Library has been developed as a mixed mode C++ project, combining together managed and unmanaged code and delivering the best of both worlds; the speed of native C++ code and the feature-rich and easy to use environment of the .NET Framework.
==================================== Bluebit .NET Matrix Library - 32 bit ==================================== This is a free version of .NET Matrix Library (NML™) which will allow matrix sizes up to 1000 x 1000. The Bluebit .NET Matrix Library (NML™) provides classes for object-oriented linear algebra in the .NET platform. It can be used to solve systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalues and eigenvectors problems, and singular value problems. Also provided are the associated matrix factorizations such as Eigen, LQ, LU, Cholesky, QR, SVD. .NET Matrix Library (NML™) also supports sparse matrices and advanced methods for solving large sparse systems of linear equations. The above functionality is present for both real and complex matrices. Two analogous sets of classes are provided for real and complex matrices, vectors and factorizations. While exposing an easy to use and powerful interface, the Bluebit .NET Matrix Library does not sacrifice any performance. Highly optimized BLAS and the standard LAPACK routines are used within the library and provide fast execution and accurate calculations. The Bluebit .NET Matrix Library has been developed as a mixed mode C++ project, combining together managed and unmanaged code and delivering the best of both worlds; the speed of native C++ code and the feature-rich and easy to use environment of the .NET Framework.