matrix-sized VS MathNet

Compare matrix-sized vs MathNet and see what are their differences.

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matrix-sized MathNet
- 6
0 3,390
- 1.2%
0.0 4.8
over 1 year ago about 1 month ago
C++ C#
BSD 3-clause "New" or "Revised" License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

matrix-sized

Posts with mentions or reviews of matrix-sized. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning matrix-sized yet.
Tracking mentions began in Dec 2020.

MathNet

Posts with mentions or reviews of MathNet. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-05.

What are some alternatives?

When comparing matrix-sized and MathNet you can also consider the following projects:

fms_blas - Lightweight BLAS (and some LAPACK) wrapper.

MKL.NET - A simple cross platform .NET API for Intel MKL

matrix-lens - Optics for the 'matrix' package.

AngouriMath - New open-source cross-platform symbolic algebra library for C# and F#. Can be used for both production and research purposes.

monolish - monolish: MONOlithic LInear equation Solvers for Highly-parallel architecture

Microsoft Automatic Graph Layout - A set of tools for graph layout and viewing

matrix-static - Wrapper around matrix that adds matrix sizes to the type-level

UnitConversion - Expansible Unit Conversion Library for .Net Core and .Net Framework

Matrix - Easy-to-use Scientific Computing library in/for C++ available for Linux and Windows.

AutoDiff - A .NET library that provides fast, accurate and automatic differentiation (computes derivative / gradient) of mathematical functions.

spidr - Accelerated machine learning with dependent types

Rationals - 🔟 Implementation of rational number arithmetic for .NET with arbitrary precision.