Models built with TensorFlow
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autoencoder
compression
differential_privacy
im2txt
inception
lm_1b
namignizer
neural_gpu
neural_programmer
next_frame_prediction
real_nvp
resnet
slim
street
swivel
syntaxnet
textsum
transformer
tutorials
video_prediction
.gitignore
.gitmodules
AUTHORS
CONTRIBUTING.md
LICENSE
README.md
WORKSPACE

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
  • differential_privacy -- privacy-preserving student models from multiple teachers
  • im2txt -- image-to-text neural network for image captioning.
  • inception -- deep convolutional networks for computer vision
  • namignizer -- recognize and generate names
  • neural_gpu -- highly parallel neural computer
  • neural_programmer -- neural network augmented with logic and mathematic operations.
  • 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