DiffSharp.Backends.Reference 1.0.7

dotnet add package DiffSharp.Backends.Reference --version 1.0.7
                    
NuGet\Install-Package DiffSharp.Backends.Reference -Version 1.0.7
                    
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" />
                    
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" />
                    
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
                    
#r "nuget: DiffSharp.Backends.Reference, 1.0.7"
                    
#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
                    
Install as a Cake Addin
#tool nuget:?package=DiffSharp.Backends.Reference&version=1.0.7
                    
Install 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.  net10.0 was computed.  net10.0-android was computed.  net10.0-browser was computed.  net10.0-ios was computed.  net10.0-maccatalyst was computed.  net10.0-macos was computed.  net10.0-tvos was computed.  net10.0-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 6,005 3/26/2022
1.0.7-preview2044360861 409 3/26/2022
1.0.7-preview1873603133 497 2/21/2022
1.0.7-preview1872895008 433 2/20/2022
1.0.7-preview1872194677 434 2/20/2022
1.0.7-preview1867437105 407 2/19/2022
1.0.7-preview1838897476 463 2/14/2022
1.0.7-preview1838869913 440 2/14/2022
1.0.6 6,658 2/9/2022
1.0.6-preview1838805210 469 2/14/2022
1.0.6-preview1838790927 495 2/14/2022
1.0.6-preview1838781533 491 2/14/2022
1.0.6-preview1838761310 420 2/14/2022
1.0.6-preview1838574327 519 2/14/2022
1.0.6-preview1838238393 461 2/13/2022
1.0.6-preview1837967313 459 2/13/2022
1.0.6-preview1837932839 314 2/13/2022
1.0.6-preview1837857091 329 2/13/2022
1.0.5 3,629 2/9/2022
1.0.4 3,833 2/8/2022
1.0.3 4,914 2/8/2022
1.0.2 4,019 2/8/2022
1.0.1 4,880 11/8/2021
1.0.0-preview-987646120 623 6/30/2021
1.0.0-preview-964642900 592 6/23/2021
1.0.0-preview-964597118 461 6/23/2021
1.0.0-preview-964532207 517 6/23/2021
1.0.0-preview-964414624 502 6/23/2021
1.0.0-preview-962665709 355 6/23/2021
1.0.0-preview-961120541 404 6/22/2021
1.0.0-preview-958984202 470 6/22/2021
1.0.0-preview-783523654 578 4/25/2021
1.0.0-preview-783503343 533 4/25/2021
1.0.0-preview-783410550 515 4/25/2021
1.0.0-preview-781810429 439 4/25/2021
1.0.0-preview-775752139 535 4/22/2021
1.0.0-preview-774228953 506 4/22/2021
1.0.0-preview-769092916 556 4/21/2021
1.0.0-preview-768013090 490 4/20/2021
1.0.0-preview-762002995 463 4/19/2021
1.0.0-preview-761040762 531 4/18/2021
1.0.0-preview-761018834 523 4/18/2021
1.0.0-preview-756065403 445 4/16/2021
1.0.0-preview-755638011 497 4/16/2021
1.0.0-preview-752421465 501 4/15/2021
1.0.0-preview-748176085 497 4/14/2021
1.0.0-preview-746203897 453 4/13/2021
1.0.0-preview-746138300 495 4/13/2021
1.0.0-preview-745205599 468 4/13/2021
1.0.0-preview-739671157 501 4/12/2021
1.0.0-preview-712483117 525 4/2/2021
1.0.0-preview-699281085 447 3/29/2021
1.0.0-preview-699125312 478 3/29/2021
1.0.0-preview-698458610 534 3/29/2021
1.0.0-preview-697743517 554 3/29/2021
1.0.0-preview-697665469 517 3/29/2021
1.0.0-preview-690194555 515 3/26/2021
1.0.0-preview-688124591 488 3/25/2021
1.0.0-preview-687886352 446 3/25/2021
1.0.0-preview-681551353 484 3/24/2021
1.0.0-preview-681104545 499 3/23/2021
1.0.0-preview-680643606 532 3/23/2021
1.0.0-preview-679950457 502 3/23/2021
1.0.0-preview-669022451 333 3/19/2021
1.0.0-preview-643151273 337 3/11/2021
1.0.0-preview-633398743 331 3/8/2021
1.0.0-preview-633348953 368 3/8/2021
1.0.0-preview-621803110 365 3/4/2021
1.0.0-preview-611561611 330 3/1/2021
1.0.0-preview-611172961 329 3/1/2021
1.0.0-preview-593196134 315 2/23/2021
1.0.0-preview-589424126 324 2/22/2021
1.0.0-preview-589402583 308 2/22/2021
1.0.0-preview-586837684 346 2/21/2021
1.0.0-preview-586440747 338 2/21/2021
1.0.0-preview-498549439 373 1/20/2021
1.0.0-preview-485581354 355 1/14/2021
1.0.0-preview-392545720 419 11/30/2020
1.0.0-preview-392233243 414 11/30/2020
1.0.0-preview-392187079 444 11/30/2020
1.0.0-preview-390203270 419 11/29/2020
1.0.0-preview-387146713 399 11/27/2020
1.0.0-preview-386097798 439 11/26/2020
1.0.0-preview-385867359 434 11/26/2020
1.0.0-preview-385523380 369 11/26/2020
1.0.0-preview-384128234 455 11/25/2020
1.0.0-preview-374537774 380 11/20/2020
1.0.0-preview-374468367 385 11/20/2020
1.0.0-preview-368681212 436 11/17/2020
1.0.0-preview-368659044 437 11/17/2020
1.0.0-preview-364746088 479 11/15/2020
1.0.0-preview-364706087 467 11/15/2020
1.0.0-preview-363372268 389 11/14/2020
1.0.0-preview-362038354 414 11/13/2020
1.0.0-preview-362004577 389 11/13/2020
1.0.0-preview-361488593 386 11/13/2020
1.0.0-preview-360710530 387 11/13/2020
1.0.0-preview-359756455 399 11/12/2020
1.0.0-preview-358333968 426 11/11/2020
1.0.0-preview-358184921 425 11/11/2020
1.0.0-preview-358174946 456 11/11/2020
1.0.0-preview-349704450 513 11/6/2020
1.0.0-preview-349564717 450 11/6/2020
1.0.0-preview-343634015 465 11/3/2020
1.0.0-preview-343610434 448 11/3/2020
1.0.0-preview-328097867 665 10/26/2020
1.0.0-preview-322875134 462 10/22/2020
1.0.0-preview-315311536 450 10/19/2020
1.0.0-preview-309180753 441 10/15/2020
1.0.0-preview-309013019 464 10/15/2020
1.0.0-preview-308920132 409 10/15/2020
1.0.0-preview-308837132 441 10/15/2020
1.0.0-preview-308751690 429 10/15/2020
1.0.0-preview-308593840 435 10/15/2020
1.0.0-preview-299173506 509 10/10/2020
1.0.0-preview-292259854 518 10/6/2020
1.0.0-preview-291985511 462 10/6/2020
1.0.0-preview-291903007 433 10/6/2020
1.0.0-preview-291722399 462 10/6/2020
1.0.0-preview-284981464 441 10/2/2020
1.0.0-preview-284595614 388 10/2/2020
1.0.0-preview-280886714 488 9/30/2020
1.0.0-preview-278989673 423 9/29/2020
1.0.0-preview-277686264 441 9/29/2020
1.0.0-preview-277653295 472 9/29/2020
1.0.0-preview-275730148 487 9/28/2020
1.0.0-preview-275727262 451 9/28/2020
1.0.0-preview-267667710 496 9/22/2020
1.0.0-preview-263264614 548 9/20/2020
1.0.0-preview-263250971 560 9/20/2020
1.0.0-preview-262623253 439 9/19/2020
1.0.0-preview-258339834 485 9/16/2020
1.0.0-preview-258210544 513 9/16/2020
1.0.0-preview-258177528 500 9/16/2020
1.0.0-preview-258119380 498 9/16/2020
1.0.0-preview-256594931 469 9/16/2020
1.0.0-preview-256435175 551 9/15/2020
1.0.0-preview-253816091 451 9/14/2020
1.0.0-preview-253197654 451 9/14/2020
1.0.0-preview-247523274 482 9/10/2020
1.0.0-preview-247118168 448 9/9/2020
1.0.0-preview-246444372 549 9/9/2020
1.0.0-preview-246434361 529 9/9/2020
1.0.0-preview-246402060 433 9/9/2020
1.0.0-preview-245105781 433 9/8/2020
1.0.0-preview-244918410 484 9/8/2020
1.0.0-preview-243478925 422 9/7/2020
1.0.0-preview-243471084 406 9/7/2020
1.0.0-preview-243323135 528 9/7/2020
1.0.0-preview-1413494063 499 11/2/2021
1.0.0-preview-1405354284 474 10/31/2021
1.0.0-preview-1338129467 498 10/13/2021
1.0.0-preview-1327345305 595 10/11/2021
1.0.0-preview-1325686991 470 10/10/2021
1.0.0-preview-1324682939 610 10/10/2021
1.0.0-preview-1239345497 550 9/15/2021
1.0.0-preview-1227879651 538 9/13/2021
1.0.0-preview-1227810778 529 9/13/2021
1.0.0-preview-1222163389 499 9/10/2021
1.0.0-preview-1177844564 516 8/28/2021
1.0.0-preview-1176119659 442 8/28/2021
1.0.0-preview-1176116073 486 8/28/2021
1.0.0-preview-1176112166 458 8/28/2021
1.0.0-preview-1172193368 437 8/26/2021
1.0.0-preview-1168287221 439 8/25/2021
1.0.0-preview-1147185155 540 8/19/2021
1.0.0-preview-1133286135 534 8/15/2021
1.0.0-preview-1118120224 549 8/10/2021
1.0.0-preview-1111420036 443 8/9/2021
1.0.0-preview-1111385512 431 8/9/2021
1.0.0-preview-1111166736 463 8/9/2021
1.0.0-preview-1088380884 488 8/1/2021
1.0.0-preview-1088311063 479 8/1/2021
1.0.0-preview-1088021240 591 8/1/2021
1.0.0-preview-1083990424 497 7/31/2021
1.0.0-preview-1080710191 484 7/30/2021
1.0.0-preview-1080701269 506 7/30/2021
1.0.0-preview-1079028054 538 7/29/2021
1.0.0-preview-1079000079 510 7/29/2021
1.0.0-preview-1078977564 565 7/29/2021
1.0.0-preview-1069218438 422 7/26/2021
1.0.0-preview-1065692127 551 7/26/2021
1.0.0-preview-1054554829 496 7/22/2021
1.0.0-preview-1054460177 489 7/22/2021
1.0.0-preview-1044919966 438 7/19/2021
1.0.0-preview-1043697034 417 7/19/2021
1.0.0-preview-1001211231 483 7/5/2021
1.0.0-preview-1001204475 478 7/5/2021
0.9.5-preview-243240046 501 9/7/2020
0.9.5-preview-243219862 488 9/7/2020