Pinned Loading
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FaceRecognition
FaceRecognition PublicFace Recognition in real-world images [ICASSP 2017]
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atom-unsaved-changes
atom-unsaved-changes PublicForked from crankyOldCanuck/unsaved-changes
An Atom package that shows unsaved changes in active editor
CoffeeScript 5
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WassersteinGAN.torch
WassersteinGAN.torch PublicTorch implementation of Wasserstein GAN https://arxiv.org/abs/1701.07875
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MeanFieldSGD
MeanFieldSGD PublicCode for the paper "Quantitative Propagation of Chaos for SGD in Wide Neural Networks"
Jupyter Notebook
Pinned Loading
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FaceRecognition
FaceRecognition PublicFace Recognition in real-world images [ICASSP 2017]
-
atom-unsaved-changes
atom-unsaved-changes PublicForked from crankyOldCanuck/unsaved-changes
An Atom package that shows unsaved changes in active editor
CoffeeScript 5
-
-
WassersteinGAN.torch
WassersteinGAN.torch PublicTorch implementation of Wasserstein GAN https://arxiv.org/abs/1701.07875
-
MeanFieldSGD
MeanFieldSGD PublicCode for the paper "Quantitative Propagation of Chaos for SGD in Wide Neural Networks"
Jupyter Notebook
Pinned Loading
-
FaceRecognition
FaceRecognition PublicFace Recognition in real-world images [ICASSP 2017]
-
atom-unsaved-changes
atom-unsaved-changes PublicForked from crankyOldCanuck/unsaved-changes
An Atom package that shows unsaved changes in active editor
CoffeeScript 5
-
-
WassersteinGAN.torch
WassersteinGAN.torch PublicTorch implementation of Wasserstein GAN https://arxiv.org/abs/1701.07875
-
MeanFieldSGD
MeanFieldSGD PublicCode for the paper "Quantitative Propagation of Chaos for SGD in Wide Neural Networks"
Jupyter Notebook
Pinned Loading
-
FaceRecognition
FaceRecognition PublicFace Recognition in real-world images [ICASSP 2017]
-
atom-unsaved-changes
atom-unsaved-changes PublicForked from crankyOldCanuck/unsaved-changes
An Atom package that shows unsaved changes in active editor
CoffeeScript 5
-
-
WassersteinGAN.torch
WassersteinGAN.torch PublicTorch implementation of Wasserstein GAN https://arxiv.org/abs/1701.07875
-
MeanFieldSGD
MeanFieldSGD PublicCode for the paper "Quantitative Propagation of Chaos for SGD in Wide Neural Networks"
Jupyter Notebook
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