- Network quantization
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SqueezeNet:
- Paper: https://arxiv.org/pdf/1602.07360.pdf
- Code: https://github.com/DeepScale/SqueezeNet (Official, Caffe) https://github.com/vonclites/squeezenet (Unofficial, TF) https://github.com/avoroshilov/tf-squeezenet (Unofficial, TF) + more
- Status:
-
XNORNet:
- Paper: https://arxiv.org/pdf/1603.05279.pdf
- Code: https://github.com/allenai/XNOR-Net (Official, Torch) not supported in TF due to an issue: tensorflow/tensorflow#1592 https://github.com/AngusG/tensorflow-xnor-bnn (may work)
- Status:
-
MobileNet:
- Paper: https://arxiv.org/pdf/1704.04861.pdf
- Code: https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet_v1.py (Official, TF, Object Detection API) https://github.com/Zehaos/MobileNet (Unofficial, TF)
- Status:
- Network prunning
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Deep Roots:
- Paper: https://arxiv.org/pdf/1605.06489.pdf
- Code: https://github.com/facebook/fb.resnet.torch (Official, Torch, ResNet?, should read paper) Not found any unofficial TF version yet
- Status:
-
ShuffleNet::
- Dark Knowledge
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Distillation:
- Paper: https://arxiv.org/pdf/1503.02531.pdf
- Code: https://github.com/chengshengchan/model_compression (Unofficial, TF) https://github.com/akamaus/mnist-distill (Unofficial, TF)
- Status:
-
FitNets:
- Paper: https://arxiv.org/pdf/1412.6550.pdf
- Code: https://github.com/adri-romsor/FitNets (Official, Theano + pylearn2) https://github.com/lisa-lab/pylearn2/tree/master/pylearn2/scripts/papers/maxout (Official, Theano + pylearn2 , Teacher)
- Status:
-
Adversarial compression:
- Status:
- http://machinethink.net/blog/compressing-deep-neural-nets/
- Deep Model Compression: https://arxiv.org/pdf/1610.09650.pdf
- Efficient Inference Engine on Compressed Deep Neural Network: https://arxiv.org/pdf/1602.01528.pdf
- Distillation: https://github.com/iRapha/replayed_distillation (Very recent, check later, paper not released yet)