This repository contains machine learning models implemented in TensorFlow. The models are maintained by their respective authors. To propose a model for inclusion, please submit a pull request.

Nicolas Papernot a66b9e13c9 added semi-supervised training of the student using improved-gan (#655) 9 anni fa
.github dc7791d01c Create ISSUE_TEMPLATE.md (#124) 9 anni fa
autoencoder a472ac9525 merged changes from #25 10 anni fa
compression 199db00e33 Merge pull request #510 from nickj-google/master 9 anni fa
differential_privacy a66b9e13c9 added semi-supervised training of the student using improved-gan (#655) 9 anni fa
im2txt 0cba7a4b5d Remove comment that TensorFlow must be built from source. 9 anni fa
inception bf51d43420 fix module object has no attribute NodeDef for tensorflow 0.11 (#572) 9 anni fa
lm_1b fdc4ce37a4 Fix README 9 anni fa
namignizer 76f567df5f add the namignizer model (#147) 9 anni fa
neural_gpu a803bf4171 Add to neural_gpu documentation. 9 anni fa
resnet d93ffd0b69 Allow softplacement for ResNet 9 anni fa
slim 804d90f75f Implementation of Inception V4 9 anni fa
street f42469ef90 Updated download instructions to match reality 9 anni fa
swivel f3144eb061 Add sys.stdout.flush() 9 anni fa
syntaxnet 5eff490de4 Fix POS tagging score of Ling et al.(2005) 9 anni fa
textsum 5e875226bc Explicitly set state_is_tuple=False. 9 anni fa
transformer d816971032 Use tf.softmax_cross_entropy_with_logits to calculate loss (#181) 9 anni fa
video_prediction d67ea24901 video prediction model code 9 anni fa
.gitignore 3e6caf5ff0 Add a .gitignore file. (#164) 9 anni fa
.gitmodules 32ab5a58dd Adding SyntaxNet to tensorflow/models (#63) 9 anni fa
AUTHORS 41c52d60fe Spatial Transformer model 10 anni fa
CONTRIBUTING.md d84df16bc3 fixed contribution guidelines 10 anni fa
LICENSE 7c41e653dc Update LICENSE 10 anni fa
README.md 4f9d102483 Open source the image-to-text model based on the "Show and Tell" paper. 9 anni fa
WORKSPACE ac0829fa2b Consolidate privacy/ and differential_privacy/. 9 anni fa

README.md

TensorFlow Models

This repository contains machine learning models implemented in TensorFlow. The models are maintained by their respective authors.

To propose a model for inclusion please submit a pull request.

Models

  • autoencoder -- various autoencoders
  • inception -- deep convolutional networks for computer vision
  • namignizer -- recognize and generate names
  • neural_gpu -- highly parallel neural computer
  • privacy -- privacy-preserving student models from multiple teachers
  • resnet -- deep and wide residual networks
  • slim -- image classification models in TF-Slim
  • swivel -- the Swivel algorithm for generating word embeddings
  • syntaxnet -- neural models of natural language syntax
  • textsum -- sequence-to-sequence with attention model for text summarization.
  • transformer -- spatial transformer network, which allows the spatial manipulation of data within the network
  • im2txt -- image-to-text neural network for image captioning.