shaform / DeepNetworks

My implementations of deep neural networks for practice.

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DeepNetworks

My implementations of deep neural networks for practice.

Implemented Methods

This repository implements the following:

  • Subpixel Convolutions: paper, code
  • Translated Parametric ReLU: paper, code
  • Weight Normalization: paper, code
  • Label Smoothing: paper, code
  • Wasserstein GAN: paper, code
  • Improved Training of Wasserstein GANs: paper, code
  • Deep Regret Analytic Generative Adversarial Networks: paper, code
  • Conditional Image Synthesis With Auxiliary Classifier GANs: paper
  • Learning to Discover Cross-Domain Relations with Generative Adversarial Networks: paper, code
  • Minibatch Stat Concatenation: paper, code

Requirements

  • tensorflow >= 1.4.0
  • Python 3

About

My implementations of deep neural networks for practice.

License:Apache License 2.0


Languages

Language:Jupyter Notebook 90.8%Language:Python 9.2%