DiffSharp 0.5.8

DiffSharp is an automatic differentiation (AD) library implemented in the F# language.

AD allows exact and efficient calculation of derivatives, by systematically applying the chain rule of calculus at the elementary operator level. AD is different from numerical differentiation, which is prone to truncation and round-off errors, and symbolic differentiation, which is exact but not efficient for run-time calculations and can only handle closed-form mathematical expressions.

Using the DiffSharp library, derivative calculations (gradients, Hessians, Jacobians, directional derivatives, and matrix-free Hessian- and Jacobian-vector products) can be incorporated with minimal change into existing algorithms. Please see the API Overview page for a list of available operations.

The library is under active development by Atılım Güneş Baydin and Barak A. Pearlmutter mainly for research applications in machine learning, as part of their work at the Brain and Computation Lab, Hamilton Institute, National University of Ireland Maynooth.

There is a newer version of this package available.
See the version list below for details.
Install-Package DiffSharp -Version 0.5.8
dotnet add package DiffSharp --version 0.5.8
<PackageReference Include="DiffSharp" Version="0.5.8" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add DiffSharp --version 0.5.8
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

Release Notes

Please visit

https://github.com/gbaydin/DiffSharp/releases

for the latest release notes.

This package is not used by any popular GitHub repositories.

Version History

Version Downloads Last updated
0.8.4-beta 216 8/24/2019
0.8.3-beta 153 7/4/2019
0.8.2-beta 147 6/25/2019
0.8.1-beta 141 6/20/2019
0.8.0-beta 158 6/11/2019
0.7.7 2,649 12/25/2015
0.7.6 491 12/15/2015
0.7.5 487 12/6/2015
0.7.4 529 10/13/2015
0.7.3 458 10/6/2015
0.7.2 455 10/4/2015
0.7.1 456 10/4/2015
0.7.0 461 9/29/2015
0.6.3 990 7/18/2015
0.6.2 480 6/6/2015
0.6.1 466 6/2/2015
0.6.0 456 4/26/2015
0.5.10 484 3/27/2015
0.5.9 460 2/26/2015
0.5.8 531 2/23/2015
0.5.7 443 2/17/2015
0.5.6 479 2/13/2015
0.5.5 462 12/15/2014
0.5.4 613 11/23/2014
0.5.3 1,146 11/7/2014
0.5.2 1,162 11/4/2014
0.5.1 467 10/27/2014
0.5.0 493 10/2/2014
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