24 packages returned for Tags:"differentiation"

Deep.Net
Deep learning library for F#. Provides symbolic model differentiation, automatic differentiation and compilation to CUDA GPUs. Includes optimizers and model blocks used in deep learning. Make sure to set the platform of your project to x64.
DiffSharp: Automatic Differentiation Library
DiffSharp is an automatic differentiation (AD) library. AD allows exact and efficient calculation of derivatives, by systematically invoking the chain rule of calculus at the elementary operator level during program execution. AD is different from numerical differentiation, which is prone to... More information
NMath
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... More information
NMath - Standard Library - Windows x64
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... More information
NMath - Standard Library - Linux x64
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... More information
NMath - Standard Library - OSX x64 (alpha)
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... More information
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.
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... More information
Data Access Library for reading and writing files in commonly used formats including: R, Matlab, Text (CSV, delimited, fixed width), matrix market, stata. Part of the Extreme Optimization Numerical Libraries for .NET.
The Extreme Optimization Numerical Libraries for .NET are a set of libraries for numerical computing and data analysis. This package provides a complete implementation of linear algebra functionality for arbitrary numerical types. Supports .NET Framework 3.5, 4.0 and 4.6+, .NET Standard 1.3 and... More information
The Extreme Optimization Numerical Libraries for .NET are a set of libraries for numerical computing and data analysis. This package provides types specialized to single-precision, including complex numbers, as well as optimized implementations of single-precision linear algebra. Supports .NET... More information
The Extreme Optimization Numerical Libraries for .NET are a set of libraries for numerical computing and data analysis. This package contains the mixed-mode native provider. This is the recommended native provider for the classic .NET Framework on Windows. Supports .NET Framework 4.0 and 4.6+ on... More information
The Extreme Optimization Numerical Libraries for .NET are a set of libraries for numerical computing and data analysis. This package contains the mixed-mode native provider. This is the recommended native provider for the classic .NET Framework on Windows. Supports .NET Framework 3.5 on Windows.