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.

Neal Wu 3f74c7b419 Convert tf.op_scope to tf.name_scope, plus a few other 1.0 upgrade changes 8 年 前
.github dc7791d01c Create ISSUE_TEMPLATE.md (#124) 9 年 前
autoencoder 052e5e8b6e Converted the models repo to TF 1.0 using the upgrade script 8 年 前
compression 052e5e8b6e Converted the models repo to TF 1.0 using the upgrade script 8 年 前
differential_privacy 3f74c7b419 Convert tf.op_scope to tf.name_scope, plus a few other 1.0 upgrade changes 8 年 前
im2txt 00ffa603f2 Manually fixed many occurrences of tf.concat 8 年 前
inception 3f74c7b419 Convert tf.op_scope to tf.name_scope, plus a few other 1.0 upgrade changes 8 年 前
learning_to_remember_rare_events 3f74c7b419 Convert tf.op_scope to tf.name_scope, plus a few other 1.0 upgrade changes 8 年 前
lm_1b fdc4ce37a4 Fix README 9 年 前
namignizer 74ae822126 Remove leading space from namignizer code 8 年 前
neural_gpu 5c53534305 Manually fixed many occurrences of tf.split 8 年 前
neural_programmer 052e5e8b6e Converted the models repo to TF 1.0 using the upgrade script 8 年 前
next_frame_prediction 052e5e8b6e Converted the models repo to TF 1.0 using the upgrade script 8 年 前
real_nvp 5c53534305 Manually fixed many occurrences of tf.split 8 年 前
resnet 64254ad355 Modify the README to reflect changes 8 年 前
slim 0b8bfa849c Merge pull request #1055 from snnn/master 8 年 前
street b41ff7f1bf Remove name arguments from tf.summary.scalar 8 年 前
swivel 3f74c7b419 Convert tf.op_scope to tf.name_scope, plus a few other 1.0 upgrade changes 8 年 前
syntaxnet 00ffa603f2 Manually fixed many occurrences of tf.concat 8 年 前
textsum 3f74c7b419 Convert tf.op_scope to tf.name_scope, plus a few other 1.0 upgrade changes 8 年 前
transformer 052e5e8b6e Converted the models repo to TF 1.0 using the upgrade script 8 年 前
tutorials 0b2c5ba296 Merge pull request #1112 from zym1010/issue1083 8 年 前
video_prediction 052e5e8b6e Converted the models repo to TF 1.0 using the upgrade script 8 年 前
.gitignore 3e6caf5ff0 Add a .gitignore file. (#164) 9 年 前
.gitmodules 32ab5a58dd Adding SyntaxNet to tensorflow/models (#63) 9 年 前
AUTHORS 41c52d60fe Spatial Transformer model 9 年 前
CONTRIBUTING.md d84df16bc3 fixed contribution guidelines 9 年 前
LICENSE 7c41e653dc Update LICENSE 9 年 前
README.md 727418e4ae One more tiny change 8 年 前
WORKSPACE ac0829fa2b Consolidate privacy/ and differential_privacy/. 9 年 前

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.
  • compression: compressing and decompressing images using a pre-trained Residual GRU network.
  • 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.
  • learning_to_remember_rare_events: a large-scale life-long memory module for use in deep learning.
  • lm_1b: language modeling on the one billion word benchmark.
  • namignizer: recognize and generate names.
  • neural_gpu: highly parallel neural computer.
  • neural_programmer: neural network augmented with logic and mathematic operations.
  • next_frame_prediction: probabilistic future frame synthesis via cross convolutional networks.
  • real_nvp: density estimation using real-valued non-volume preserving (real NVP) transformations.
  • resnet: deep and wide residual networks.
  • slim: image classification models in TF-Slim.
  • street: identify the name of a street (in France) from an image using a Deep RNN.
  • 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.
  • tutorials: models described in the TensorFlow tutorials.
  • video_prediction: predicting future video frames with neural advection.