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04c3a7f5
编写于
2月 25, 2017
作者:
A
Aniruddha Tapas
提交者:
GitHub
2月 25, 2017
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...
@@ -8,16 +8,23 @@ To propose a model for inclusion please submit a pull request.
...
@@ -8,16 +8,23 @@ To propose a model for inclusion please submit a pull request.
## Models
## Models
-
[
autoencoder
](
autoencoder
)
-- various autoencoders
-
[
autoencoder
](
autoencoder
)
-- various autoencoders.
-
[
differential_privacy
](
differential_privacy
)
-- privacy-preserving student models from multiple teachers
-
[
compression
](
compression
)
-- compressing and decompressing images using pre-trained Residual GRU network.
-
[
differential_privacy
](
differential_privacy
)
-- privacy-preserving student models from multiple teachers.
-
[
im2txt
](
im2txt
)
-- image-to-text neural network for image captioning.
-
[
im2txt
](
im2txt
)
-- image-to-text neural network for image captioning.
-
[
inception
](
inception
)
-- deep convolutional networks for computer vision
-
[
lm_1b
](
lm_1b
)
-- language modelling on one billion word benchmark.
-
[
namignizer
](
namignizer
)
-- recognize and generate names
-
[
inception
](
inception
)
-- deep convolutional networks for computer vision.
-
[
neural_gpu
](
neural_gpu
)
-- highly parallel neural computer
-
[
namignizer
](
namignizer
)
-- recognize and generate names.
-
[
neural_gpu
](
neural_gpu
)
-- highly parallel neural computer.
-
[
neural_programmer
](
neural_programmer
)
-- neural network augmented with logic and mathematic operations.
-
[
neural_programmer
](
neural_programmer
)
-- neural network augmented with logic and mathematic operations.
-
[
resnet
](
resnet
)
-- deep and wide residual networks
-
[
next_frame_prediction
](
next_frame_prediction
)
-- probabilistic future frame synthesis via cross convolutional networks.
-
[
slim
](
slim
)
-- image classification models in TF-Slim
-
[
real_nvp
](
real_nvp
)
-- density estimation using real-valued non-volume preserving (real NVP).
-
[
swivel
](
swivel
)
-- the Swivel algorithm for generating word embeddings
-
[
resnet
](
resnet
)
-- deep and wide residual networks.
-
[
syntaxnet
](
syntaxnet
)
-- neural models of natural language syntax
-
[
slim
](
slim
)
-- image classification models in TF-Slim.
-
[
street
](
street
)
-- identify the name of a street (in France) from an image using Deep RNN.
-
[
swivel
](
swivel
)
-- the Swivel algorithm for generating word embeddings.
-
[
syntaxnet
](
syntaxnet
)
-- neural models of natural language syntax.
-
[
textsum
](
textsum
)
-- sequence-to-sequence with attention model for text summarization.
-
[
textsum
](
textsum
)
-- sequence-to-sequence with attention model for text summarization.
-
[
transformer
](
transformer
)
-- spatial transformer network, which allows the spatial manipulation of data within the network
-
[
transformer
](
transformer
)
-- spatial transformer network, which allows the spatial manipulation of data within the network.
-
[
tutorials
](
tutorials
)
-- models referenced to from the
[
TensorFlow tutorials
](
https://www.tensorflow.org/tutorials/
)
.
-
[
video_prediction
](
video_prediction
)
-- predicting future video frames with neural advection.
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