DiffSharp 0.5.5

DiffSharp (Diff#) 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 can be incorporated with minimal change into existing algorithms.

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There is a newer version of this package available.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 0.5.5
dotnet add package DiffSharp --version 0.5.5
<PackageReference Include="DiffSharp" Version="0.5.5" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add DiffSharp --version 0.5.5
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 263 8/24/2019
0.8.3-beta 158 7/4/2019
0.8.2-beta 153 6/25/2019
0.8.1-beta 146 6/20/2019
0.8.0-beta 163 6/11/2019
0.7.7 2,692 12/25/2015
0.7.6 500 12/15/2015
0.7.5 493 12/6/2015
0.7.4 539 10/13/2015
0.7.3 467 10/6/2015
0.7.2 463 10/4/2015
0.7.1 463 10/4/2015
0.7.0 468 9/29/2015
0.6.3 999 7/18/2015
0.6.2 487 6/6/2015
0.6.1 474 6/2/2015
0.6.0 464 4/26/2015
0.5.10 494 3/27/2015
0.5.9 468 2/26/2015
0.5.8 538 2/23/2015
0.5.7 451 2/17/2015
0.5.6 488 2/13/2015
0.5.5 471 12/15/2014
0.5.4 621 11/23/2014
0.5.3 1,153 11/7/2014
0.5.2 1,169 11/4/2014
0.5.1 473 10/27/2014
0.5.0 500 10/2/2014
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