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Top 10 wasserstein-gan open source projects

Resources and Implementations of Generative Adversarial Nets: GAN, DCGAN, WGAN, CGAN, InfoGAN

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python gan dcgan infogan wasserstein-gan adversarial-nets

Code for the paper "TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks"

✭ 67

python pytorch generative-adversarial-network wasserstein-gan gradient-penalty time-series-anomaly-detection

skip-thought-gan

Generating Text through Adversarial Training(GAN) using Skip-Thought Vectors

✭ 44

nlp data-science text-generation generative-adversarial-network gans skip-thought-vectors wasserstein-gan

chainer-wasserstein-gan

Chainer implementation of the Wesserstein GAN

✭ 20

python chainer gan wgan wasserstein-gan

Pytorch implementation of Wasserstein GANs with Gradient Penalty

✭ 161

python pytorch gan wasserstein-gan wgan-gp gradient-penalty

Improved-Wasserstein-GAN-application-on-MRI-images

Improved Wasserstein GAN (WGAN-GP) application on medical (MRI) images

✭ 23

python lasagne theano deep-learning medical-imaging generative-adversarial-network mri-images unsupervised-learning medical-images neuralnetwork wgan wasserstein-gan wgan-gp improved-wgan gan-lasagne

WassersteinGAN.torch

Torch implementation of Wasserstein GAN https://arxiv.org/abs/1701.07875

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lua deep-learning torch gan neural-networks wasserstein wasserstein-gan

progressive growing of GANs

Pure tensorflow implementation of progressive growing of GANs

✭ 31

python Jupyter Notebook tensorflow generative-adversarial-network gan wgan wasserstein-gan wgan-gp progressive-gan pggan progressively-growing-gan

progressive-growing-of-gans.pytorch

Unofficial PyTorch implementation of "Progressive Growing of GANs for Improved Quality, Stability, and Variation".

✭ 51

python generator pytorch discriminator generative-adversarial-network tensorboard wgan optimal-transport wasserstein-gan progressive-gan

ConvolutionaNeuralNetworksToEnhanceCodedSpeech

In this work we propose two postprocessing approaches applying convolutional neural networks (CNNs) either in the time domain or the cepstral domain to enhance the coded speech without any modification of the codecs. The time domain approach follows an end-to-end fashion, while the cepstral domain approach uses analysis-synthesis with cepstral d…

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python keras cnn generative-adversarial-network gan post-processing mfcc speech-processing wasserstein-gan speech-enhancement speech-reconstruction 1d-convolution

1-10 of 10 wasserstein-gan projects