MathNet.Numerics.MKL.Win-x64 2.5.0 The ID prefix of this package has been reserved for one of the owners of this package by Prefix Reserved

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See the version list below for details.
Install-Package MathNet.Numerics.MKL.Win-x64 -Version 2.5.0
dotnet add package MathNet.Numerics.MKL.Win-x64 --version 2.5.0
<PackageReference Include="MathNet.Numerics.MKL.Win-x64" Version="2.5.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add MathNet.Numerics.MKL.Win-x64 --version 2.5.0
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: MathNet.Numerics.MKL.Win-x64, 2.5.0"
#r directive can be used in F# Interactive, C# scripting and .NET Interactive. Copy this into the interactive tool or source code of the script to reference the package.
// Install MathNet.Numerics.MKL.Win-x64 as a Cake Addin
#addin nuget:?package=MathNet.Numerics.MKL.Win-x64&version=2.5.0

// Install MathNet.Numerics.MKL.Win-x64 as a Cake Tool
#tool nuget:?package=MathNet.Numerics.MKL.Win-x64&version=2.5.0
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

Intel MKL native libraries for Math.NET Numerics on Windows.

There are no supported framework assets in this package.

Learn more about Target Frameworks and .NET Standard.

This package has no dependencies.

NuGet packages (4)

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Quantum research libraries for quantum simulation (non-commercial).


Captcha Recognition for DE UI based on Nerual Nets


Nyaong C# Library Math



GitHub repositories (1)

Showing the top 1 popular GitHub repositories that depend on MathNet.Numerics.MKL.Win-x64:

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CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic Encryptions and its applications). This project demonstrates the use of Homomorphic Encryption for outsourcing neural-network predictions. The scenario in mind is a provider that would like to provide Prediction as a Service (PaaS) but the data for which predictions are needed may be private. This may be the case in fields such as health or finance. By using CryptoNets, the user of the service can encrypt their data using Homomorphic Encryption and send only the encrypted message to the service provider. Since Homomorphic Encryptions allow the provider to operate on the data while it is encrypted, the provider can make predictions using a pre-trained Neural-Network while the data remains encrypted throughout the process and finaly send the prediction to the user who can decrypt the results. During the process the service provider does not learn anything about the data that was used, the prediction that was made or any intermediate result since everything is encrypted throughout the process. This project uses the Simple Encrypted Arithmetic Library SEAL version 3.2.1 implementation of Homomorphic Encryption developed in Microsoft Research.
Version Downloads Last updated
3.0.0-beta2 33 12/29/2021
3.0.0-beta1 38 12/23/2021
2.6.0-beta3 37 12/19/2021
2.6.0-beta2 46 12/9/2021
2.5.0 21,906 1/1/2021
2.4.0 12,963 5/22/2020
2.3.0 151,128 2/14/2018
2.2.0 27,249 10/30/2016
2.1.0 1,344 9/8/2016
2.0.0 7,078 9/26/2015
1.8.0 8,356 5/9/2015
1.7.0 2,340 12/31/2014
1.6.0 1,854 6/21/2014
1.5.0 868 6/15/2014
1.4.0 1,200 3/1/2014
1.3.0 1,512 5/1/2013
1.2.1 1,361 2/4/2013
1.2.0 951 2/3/2013

r14 with Intel MKL 2020 Update 4
MKL Direct Sparse Solver provider ~Jong Hyun Kim