DiffSharp.Backends.Reference 1.0.7-preview2044360861

This is a prerelease version of DiffSharp.Backends.Reference.
There is a newer version of this package available.
See the version list below for details.
dotnet add package DiffSharp.Backends.Reference --version 1.0.7-preview2044360861
                    
NuGet\Install-Package DiffSharp.Backends.Reference -Version 1.0.7-preview2044360861
                    
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="DiffSharp.Backends.Reference" Version="1.0.7-preview2044360861" />
                    
For projects that support PackageReference, copy this XML node into the project file to reference the package.
<PackageVersion Include="DiffSharp.Backends.Reference" Version="1.0.7-preview2044360861" />
                    
Directory.Packages.props
<PackageReference Include="DiffSharp.Backends.Reference" />
                    
Project file
For projects that support Central Package Management (CPM), copy this XML node into the solution Directory.Packages.props file to version the package.
paket add DiffSharp.Backends.Reference --version 1.0.7-preview2044360861
                    
#r "nuget: DiffSharp.Backends.Reference, 1.0.7-preview2044360861"
                    
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
#addin nuget:?package=DiffSharp.Backends.Reference&version=1.0.7-preview2044360861&prerelease
                    
Install DiffSharp.Backends.Reference as a Cake Addin
#tool nuget:?package=DiffSharp.Backends.Reference&version=1.0.7-preview2044360861&prerelease
                    
Install DiffSharp.Backends.Reference as a Cake Tool

DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/

Product Compatible and additional computed target framework versions.
.NET net5.0 was computed.  net5.0-windows was computed.  net6.0 was computed.  net6.0-android was computed.  net6.0-ios was computed.  net6.0-maccatalyst was computed.  net6.0-macos was computed.  net6.0-tvos was computed.  net6.0-windows was computed.  net7.0 was computed.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 was computed.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed.  net9.0 was computed.  net9.0-android was computed.  net9.0-browser was computed.  net9.0-ios was computed.  net9.0-maccatalyst was computed.  net9.0-macos was computed.  net9.0-tvos was computed.  net9.0-windows was computed. 
.NET Core netcoreapp3.0 was computed.  netcoreapp3.1 was computed. 
.NET Standard netstandard2.1 is compatible. 
MonoAndroid monoandroid was computed. 
MonoMac monomac was computed. 
MonoTouch monotouch was computed. 
Tizen tizen60 was computed. 
Xamarin.iOS xamarinios was computed. 
Xamarin.Mac xamarinmac was computed. 
Xamarin.TVOS xamarintvos was computed. 
Xamarin.WatchOS xamarinwatchos was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages (5)

Showing the top 5 NuGet packages that depend on DiffSharp.Backends.Reference:

Package Downloads
DiffSharp-cuda-windows

DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/

DiffSharp-cuda-linux

DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/

DiffSharp-cpu

DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/

DiffSharp-lite

DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/

FAkka.Mathnet.Symbolic.withTensorSupported

Package Description

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last updated
1.0.7 5,959 3/26/2022
1.0.7-preview2044360861 386 3/26/2022
1.0.7-preview1873603133 471 2/21/2022
1.0.7-preview1872895008 410 2/20/2022
1.0.7-preview1872194677 411 2/20/2022
1.0.7-preview1867437105 384 2/19/2022
1.0.7-preview1838897476 433 2/14/2022
1.0.7-preview1838869913 418 2/14/2022
1.0.6 6,632 2/9/2022
1.0.6-preview1838805210 442 2/14/2022
1.0.6-preview1838790927 472 2/14/2022
1.0.6-preview1838781533 465 2/14/2022
1.0.6-preview1838761310 393 2/14/2022
1.0.6-preview1838574327 495 2/14/2022
1.0.6-preview1838238393 437 2/13/2022
1.0.6-preview1837967313 433 2/13/2022
1.0.6-preview1837932839 287 2/13/2022
1.0.6-preview1837857091 303 2/13/2022
1.0.5 3,599 2/9/2022
1.0.4 3,808 2/8/2022
1.0.3 4,885 2/8/2022
1.0.2 3,995 2/8/2022
1.0.1 4,853 11/8/2021
1.0.0-preview-987646120 601 6/30/2021
1.0.0-preview-964642900 568 6/23/2021
1.0.0-preview-964597118 434 6/23/2021
1.0.0-preview-964532207 494 6/23/2021
1.0.0-preview-964414624 478 6/23/2021
1.0.0-preview-962665709 328 6/23/2021
1.0.0-preview-961120541 380 6/22/2021
1.0.0-preview-958984202 445 6/22/2021
1.0.0-preview-783523654 550 4/25/2021
1.0.0-preview-783503343 505 4/25/2021
1.0.0-preview-783410550 486 4/25/2021
1.0.0-preview-781810429 411 4/25/2021
1.0.0-preview-775752139 504 4/22/2021
1.0.0-preview-774228953 466 4/22/2021
1.0.0-preview-769092916 525 4/21/2021
1.0.0-preview-768013090 456 4/20/2021
1.0.0-preview-762002995 434 4/19/2021
1.0.0-preview-761040762 504 4/18/2021
1.0.0-preview-761018834 493 4/18/2021
1.0.0-preview-756065403 415 4/16/2021
1.0.0-preview-755638011 466 4/16/2021
1.0.0-preview-752421465 464 4/15/2021
1.0.0-preview-748176085 468 4/14/2021
1.0.0-preview-746203897 426 4/13/2021
1.0.0-preview-746138300 469 4/13/2021
1.0.0-preview-745205599 440 4/13/2021
1.0.0-preview-739671157 471 4/12/2021
1.0.0-preview-712483117 498 4/2/2021
1.0.0-preview-699281085 419 3/29/2021
1.0.0-preview-699125312 450 3/29/2021
1.0.0-preview-698458610 505 3/29/2021
1.0.0-preview-697743517 525 3/29/2021
1.0.0-preview-697665469 488 3/29/2021
1.0.0-preview-690194555 487 3/26/2021
1.0.0-preview-688124591 461 3/25/2021
1.0.0-preview-687886352 413 3/25/2021
1.0.0-preview-681551353 455 3/24/2021
1.0.0-preview-681104545 466 3/23/2021
1.0.0-preview-680643606 505 3/23/2021
1.0.0-preview-679950457 474 3/23/2021
1.0.0-preview-669022451 306 3/19/2021
1.0.0-preview-643151273 303 3/11/2021
1.0.0-preview-633398743 301 3/8/2021
1.0.0-preview-633348953 340 3/8/2021
1.0.0-preview-621803110 333 3/4/2021
1.0.0-preview-611561611 300 3/1/2021
1.0.0-preview-611172961 301 3/1/2021
1.0.0-preview-593196134 288 2/23/2021
1.0.0-preview-589424126 297 2/22/2021
1.0.0-preview-589402583 279 2/22/2021
1.0.0-preview-586837684 316 2/21/2021
1.0.0-preview-586440747 311 2/21/2021
1.0.0-preview-498549439 344 1/20/2021
1.0.0-preview-485581354 328 1/14/2021
1.0.0-preview-392545720 390 11/30/2020
1.0.0-preview-392233243 386 11/30/2020
1.0.0-preview-392187079 412 11/30/2020
1.0.0-preview-390203270 390 11/29/2020
1.0.0-preview-387146713 368 11/27/2020
1.0.0-preview-386097798 407 11/26/2020
1.0.0-preview-385867359 394 11/26/2020
1.0.0-preview-385523380 335 11/26/2020
1.0.0-preview-384128234 425 11/25/2020
1.0.0-preview-374537774 350 11/20/2020
1.0.0-preview-374468367 356 11/20/2020
1.0.0-preview-368681212 407 11/17/2020
1.0.0-preview-368659044 403 11/17/2020
1.0.0-preview-364746088 448 11/15/2020
1.0.0-preview-364706087 436 11/15/2020
1.0.0-preview-363372268 360 11/14/2020
1.0.0-preview-362038354 385 11/13/2020
1.0.0-preview-362004577 359 11/13/2020
1.0.0-preview-361488593 356 11/13/2020
1.0.0-preview-360710530 357 11/13/2020
1.0.0-preview-359756455 371 11/12/2020
1.0.0-preview-358333968 397 11/11/2020
1.0.0-preview-358184921 394 11/11/2020
1.0.0-preview-358174946 421 11/11/2020
1.0.0-preview-349704450 484 11/6/2020
1.0.0-preview-349564717 418 11/6/2020
1.0.0-preview-343634015 431 11/3/2020
1.0.0-preview-343610434 420 11/3/2020
1.0.0-preview-328097867 629 10/26/2020
1.0.0-preview-322875134 429 10/22/2020
1.0.0-preview-315311536 421 10/19/2020
1.0.0-preview-309180753 414 10/15/2020
1.0.0-preview-309013019 436 10/15/2020
1.0.0-preview-308920132 378 10/15/2020
1.0.0-preview-308837132 412 10/15/2020
1.0.0-preview-308751690 400 10/15/2020
1.0.0-preview-308593840 405 10/15/2020
1.0.0-preview-299173506 479 10/10/2020
1.0.0-preview-292259854 484 10/6/2020
1.0.0-preview-291985511 431 10/6/2020
1.0.0-preview-291903007 403 10/6/2020
1.0.0-preview-291722399 426 10/6/2020
1.0.0-preview-284981464 410 10/2/2020
1.0.0-preview-284595614 357 10/2/2020
1.0.0-preview-280886714 452 9/30/2020
1.0.0-preview-278989673 394 9/29/2020
1.0.0-preview-277686264 410 9/29/2020
1.0.0-preview-277653295 439 9/29/2020
1.0.0-preview-275730148 458 9/28/2020
1.0.0-preview-275727262 423 9/28/2020
1.0.0-preview-267667710 462 9/22/2020
1.0.0-preview-263264614 519 9/20/2020
1.0.0-preview-263250971 530 9/20/2020
1.0.0-preview-262623253 406 9/19/2020
1.0.0-preview-258339834 456 9/16/2020
1.0.0-preview-258210544 482 9/16/2020
1.0.0-preview-258177528 470 9/16/2020
1.0.0-preview-258119380 469 9/16/2020
1.0.0-preview-256594931 440 9/16/2020
1.0.0-preview-256435175 519 9/15/2020
1.0.0-preview-253816091 412 9/14/2020
1.0.0-preview-253197654 418 9/14/2020
1.0.0-preview-247523274 445 9/10/2020
1.0.0-preview-247118168 414 9/9/2020
1.0.0-preview-246444372 518 9/9/2020
1.0.0-preview-246434361 499 9/9/2020
1.0.0-preview-246402060 398 9/9/2020
1.0.0-preview-245105781 404 9/8/2020
1.0.0-preview-244918410 453 9/8/2020
1.0.0-preview-243478925 392 9/7/2020
1.0.0-preview-243471084 373 9/7/2020
1.0.0-preview-243323135 499 9/7/2020
1.0.0-preview-1413494063 475 11/2/2021
1.0.0-preview-1405354284 447 10/31/2021
1.0.0-preview-1338129467 473 10/13/2021
1.0.0-preview-1327345305 570 10/11/2021
1.0.0-preview-1325686991 447 10/10/2021
1.0.0-preview-1324682939 586 10/10/2021
1.0.0-preview-1239345497 529 9/15/2021
1.0.0-preview-1227879651 510 9/13/2021
1.0.0-preview-1227810778 507 9/13/2021
1.0.0-preview-1222163389 474 9/10/2021
1.0.0-preview-1177844564 495 8/28/2021
1.0.0-preview-1176119659 417 8/28/2021
1.0.0-preview-1176116073 460 8/28/2021
1.0.0-preview-1176112166 434 8/28/2021
1.0.0-preview-1172193368 412 8/26/2021
1.0.0-preview-1168287221 414 8/25/2021
1.0.0-preview-1147185155 506 8/19/2021
1.0.0-preview-1133286135 506 8/15/2021
1.0.0-preview-1118120224 521 8/10/2021
1.0.0-preview-1111420036 418 8/9/2021
1.0.0-preview-1111385512 409 8/9/2021
1.0.0-preview-1111166736 440 8/9/2021
1.0.0-preview-1088380884 466 8/1/2021
1.0.0-preview-1088311063 456 8/1/2021
1.0.0-preview-1088021240 565 8/1/2021
1.0.0-preview-1083990424 473 7/31/2021
1.0.0-preview-1080710191 459 7/30/2021
1.0.0-preview-1080701269 479 7/30/2021
1.0.0-preview-1079028054 515 7/29/2021
1.0.0-preview-1079000079 486 7/29/2021
1.0.0-preview-1078977564 536 7/29/2021
1.0.0-preview-1069218438 398 7/26/2021
1.0.0-preview-1065692127 522 7/26/2021
1.0.0-preview-1054554829 471 7/22/2021
1.0.0-preview-1054460177 468 7/22/2021
1.0.0-preview-1044919966 410 7/19/2021
1.0.0-preview-1043697034 392 7/19/2021
1.0.0-preview-1001211231 451 7/5/2021
1.0.0-preview-1001204475 453 7/5/2021
0.9.5-preview-243240046 469 9/7/2020
0.9.5-preview-243219862 459 9/7/2020