Comparison of deep learning software (English Wikipedia)

Atilim Gunes Baydin; Barak A. Pearlmutter; Alexey Andreyevich Radul; Jeffrey Mark Siskind (20 February 2015). "Automatic differentiation in machine learning: a survey". arXiv:1502.05767 [cs.LG].

berkeleyvision.org

caffe.berkeleyvision.org

"Caffe | Model Zoo". caffe.berkeleyvision.org.

cntk.ai

"CNTK - Computational Network Toolkit". Microsoft Corporation.

collobert.com

ronan.collobert.com

"Torch7: A Matlab-like Environment for Machine Learning" (PDF).

deeplearning.net

"Using the GPU — Theano 0.8.2 documentation". Archived from the original on 2017-04-01. Retrieved 2016-01-21.
"gradient – Symbolic Differentiation — Theano 1.0.0 documentation". deeplearning.net.
"Using multiple GPUs — Theano 1.0.0 documentation". deeplearning.net.

deeplearning4j.org

"Comparing Top Deep Learning Frameworks". Deeplearning4j. Archived from the original on 2017-11-07. Retrieved 2017-10-31.
Chris Nicholson; Adam Gibson. "Deeplearning4j Models". Archived from the original on 2017-02-11. Retrieved 2016-03-02.
Deeplearning4j. "Deeplearning4j on Spark". Deeplearning4j. Archived from the original on 2017-07-13. Retrieved 2016-09-01.{{cite web}}: CS1 maint: numeric names: authors list (link)

github.com

"Microsoft/caffe". GitHub. 30 October 2021.
"Caffe: a fast open framework for deep learning". July 19, 2019 – via GitHub.
GitHub - BVLC/caffe: Caffe: a fast open framework for deep learning., Berkeley Vision and Learning Center, 2019-09-25, retrieved 2019-09-25
"Support for Open CL · Issue #27 · deeplearning4j/nd4j". GitHub.
"Metalhead". FluxML. 29 October 2021.
"Is there RBM in Keras? · Issue #461 · keras-team/keras". GitHub.
"Does Keras support using multiple GPUs? · Issue #2436 · keras-team/keras". GitHub.
"CNTK/LICENSE.md at master · Microsoft/CNTK · GitHub". GitHub.
"Setup CNTK on your machine". GitHub.
"CNTK usage overview". GitHub.
"BrainScript Network Builder". GitHub.
".NET Support · Issue #960 · Microsoft/CNTK". GitHub.
"How to train a model using multiple machines? · Issue #59 · Microsoft/CNTK". GitHub.
"Prebuilt models for image classification · Issue #140 · microsoft/CNTK". GitHub.
"Restricted Boltzmann Machine with CNTK #534". GitHub, Inc. 27 May 2016. Retrieved 30 October 2023.
"Multiple GPUs and machines". Microsoft Corporation.
"Disclaimer". CNTK TEAM. 6 November 2021.
"Releases · dmlc/mxnet". Github.
"MXNet.js". Github. 28 October 2021.
"Model Gallery". GitHub. 29 October 2022.
"OpenCL build of pytorch: (in-progress, not useable) - hughperkins/pytorch-coriander". July 14, 2019 – via GitHub.
"DLPrimitives/OpenCL out of tree backend for pytorch - artyom-beilis/pytorch_dlprim". Jan 21, 2022 – via GitHub.
"OpenCL Support · Issue #488 · pytorch/pytorch". GitHub.
"Restricted Boltzmann Machines (RBMs) in PyTorch". GitHub. 14 November 2022.
"tensorflow/roadmap.md at master · tensorflow/tensorflow · GitHub". GitHub. January 23, 2017. Retrieved May 21, 2017.
"OpenCL support · Issue #22 · tensorflow/tensorflow". GitHub.
"Models and examples built with TensorFlow". July 19, 2019 – via GitHub.
"Recipes/modelzoo at master · Lasagne/Recipes · GitHub". GitHub.
"torch/torch7". July 18, 2019 – via GitHub.
"GitHub - soumith/torch-android: Torch-7 for Android". GitHub. 13 October 2021.
"GitHub - jonathantompson/jtorch: An OpenCL Torch Utility Library". GitHub. 18 November 2020.
"Cheatsheet". GitHub.
"cltorch". GitHub.
"Torch CUDA backend". GitHub.
"Torch CUDA backend for nn". GitHub.
"Autograd automatically differentiates native Torch code: twitter/torch-autograd". July 9, 2019 – via GitHub.
"ModelZoo". GitHub.

googleblog.com

developers.googleblog.com

"TensorFlow 0.12 adds support for Windows".

groups.google.com

"Automatic vs. Symbolic differentiation".

intel.com

software.intel.com

"Intel® Data Analytics Acceleration Library (Intel® DAAL)". software.intel.com. November 20, 2018.
"Intel® Math Kernel Library (Intel® MKL)". software.intel.com. September 11, 2018.
"Deep Neural Network Functions". software.intel.com. May 24, 2019.
"Using Intel® MKL with Threaded Applications". software.intel.com. June 1, 2017.
"Intel® Xeon Phi™ Delivers Competitive Performance For Deep Learning—And Getting Better Fast". software.intel.com. March 21, 2019.

intel.com

"Intel® Math Kernel Library Release Notes and New Features". Intel.

keras.io

"Applications - Keras Documentation". keras.io.

mathworks.com

"GPU Coder - MATLAB & Simulink". MathWorks. Retrieved 13 November 2017.
"Automatic Differentiation Background - MATLAB & Simulink". MathWorks. September 3, 2019. Retrieved November 19, 2019.
"Neural Network Toolbox - MATLAB". MathWorks. Retrieved 13 November 2017.
"Deep Learning Models - MATLAB & Simulink". MathWorks. Retrieved 13 November 2017.
"Parallel Computing Toolbox - MATLAB". MathWorks. Retrieved 13 November 2017.

mlverse.org

torch.mlverse.org

"Falbel D, Luraschi J (2023). torch: Tensors and Neural Networks with 'GPU' Acceleration". torch.mlverse.org. Retrieved 2023-11-28.

mxnet.readthedocs.io

"Installation Guide — mxnet documentation". Readthdocs.
"MXNet Smart Device". ReadTheDocs. Archived from the original on 2016-09-21. Retrieved 2016-05-19.
"— Redirecting to mxnet.io". mxnet.readthedocs.io.
"Run MXNet on Multiple CPU/GPUs with Data Parallel". GitHub.

nd4j.org

"N-Dimensional Scientific Computing for Java". Archived from the original on 2016-10-16. Retrieved 2016-02-05.

preferred.jp

Preferred Networks Migrates its Deep Learning Research Platform to PyTorch, 2019-12-05, retrieved 2019-12-27

pytorch.org

"PyTorch". Dec 17, 2021.

r-project.org

cran.r-project.org

Allaire, J.J.; Kalinowski, T.; Falbel, D.; Eddelbuettel, D.; Yuan, T.; Golding, N. (28 September 2023). "tensorflow: R Interface to 'TensorFlow'". The Comprehensive R Archive Network. Retrieved 30 October 2023.

tensorflow.org

"Install TensorFlow with pip".
"TensorFlow". TensorFlow.

web.archive.org

"Deep Learning — ROCm 4.5.0 documentation". Archived from the original on 2022-12-05. Retrieved 2022-09-27.
"N-Dimensional Scientific Computing for Java". Archived from the original on 2016-10-16. Retrieved 2016-02-05.
"Comparing Top Deep Learning Frameworks". Deeplearning4j. Archived from the original on 2017-11-07. Retrieved 2017-10-31.
Chris Nicholson; Adam Gibson. "Deeplearning4j Models". Archived from the original on 2017-02-11. Retrieved 2016-03-02.
Deeplearning4j. "Deeplearning4j on Spark". Deeplearning4j. Archived from the original on 2017-07-13. Retrieved 2016-09-01.{{cite web}}: CS1 maint: numeric names: authors list (link)
"MXNet Smart Device". ReadTheDocs. Archived from the original on 2016-09-21. Retrieved 2016-05-19.
"Using the GPU — Theano 0.8.2 documentation". Archived from the original on 2017-04-01. Retrieved 2016-01-21.
"Deep Learning — ROCm 4.5.0 documentation". Archived from the original on 2022-12-05. Retrieved 2022-09-27.

wolfram.com

blog.wolfram.com

"Launching Mathematica 10". Wolfram.

reference.wolfram.com

"Parallel Computing—Wolfram Language Documentation". reference.wolfram.com.

wolframcloud.com

resources.wolframcloud.com

"Wolfram Neural Net Repository of Neural Network Models". resources.wolframcloud.com.