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https://github.com/sunshineatnoon/Paper-Implementations

Use PyTorch to implement some classic frameworks
https://github.com/sunshineatnoon/Paper-Implementations

computer-vision deep-learning pytorch

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Use PyTorch to implement some classic frameworks

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# Paper Implementations
Use PyTorch to implement some classic papers

## Implemented

**[Classification on MNIST](https://github.com/sunshineatnoon/PyTorchExercise/tree/master/classification)**
- Two layer CNN
- Network in Network
- ResNet18

**Generative Models**
- [DCGAN](https://github.com/sunshineatnoon/PyTorchExercise/tree/master/dcgan)
- [pix2pix](https://github.com/sunshineatnoon/PyTorchExercise/tree/master/pix2pix)
- [DiscoGAN](https://github.com/sunshineatnoon/PyTorchExamples/tree/master/DiscoGAN)
- [CycleGAN](https://github.com/sunshineatnoon/Paper-Implementations/tree/master/cycleGAN)
- [BEGAN](https://github.com/sunshineatnoon/Paper-Implementations/tree/master/BEGAN)
- [VAE](https://github.com/sunshineatnoon/Paper-Implementations/tree/master/VAE)

**Neural Style Transfer**
- [Neural Style Transfer](https://github.com/sunshineatnoon/Paper-Implementations/tree/master/NeuralSytleTransfer#neural-style-transfer)
- [Preserving Color in Neural Artistic Style Transfer](https://github.com/sunshineatnoon/Paper-Implementations/tree/master/NeuralSytleTransfer#neural-style-transfer-with-color-preservation)
- [Neural Style Transfer by aligning the BN statistics](https://github.com/sunshineatnoon/Paper-Implementations/tree/master/NeuralSytleTransfer#neural-style-transfer-by-aligning-the-bn-statistics)
- [Fast Neural Style Transfer](https://github.com/sunshineatnoon/Paper-Implementations/tree/master/fast-neural-style)

**LSTM**
- [Char RNN](https://github.com/sunshineatnoon/PyTorchExamples/tree/master/char-rnn)