Topic: wgan-gp Goto Github
Some thing interesting about wgan-gp
Some thing interesting about wgan-gp
wgan-gp,Implementation of "Over-the-Air Design of GAN Training for mmWave MIMO Channel Estimation"
User: akashsdoshi96
wgan-gp,Performance comparison of ACGAN, BEGAN, CGAN, DRAGAN, EBGAN, GAN, infoGAN, LSGAN, VAE, WGAN, WGAN_GP on cifar-10
User: alicearia
wgan-gp,implement GANs and VAE using pytorch
User: assassint2017
wgan-gp,Playing with MNIST. Machine Learning. Generative Models.
User: bchao1
wgan-gp,Tensorflow Implementation of Paper "Improved Training of Wasserstein GANs"
User: changwoolee
wgan-gp,Keras model and tensorflow optimization of 'improved Training of Wasserstein GANs'
User: daigo0927
wgan-gp,Machine learning, in numpy
User: ddbourgin
Home Page: https://numpy-ml.readthedocs.io/
wgan-gp,TensorFlow 2.0 implementation of Improved Training of Wasserstein GANs
User: drewszurko
Home Page: https://arxiv.org/abs/1704.00028
wgan-gp,Pytorch implementation of Wasserstein GANs with Gradient Penalty
User: emiliendupont
wgan-gp,Pytorch implementation of a Conditional WGAN with Gradient Penalty
User: gcucurull
wgan-gp,A PyTorch implementation of SRGAN specific for Anime Super Resolution based on "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network". And another PyTorch WGAN-gp implementation of SRGAN referring to "Improved Training of Wasserstein GANs".
User: goldhuang
wgan-gp,Improved Training of Wasserstein GANs
User: hanyoseob
Home Page: https://github.com/hanyoseob/pytorch-WGAN-GP
wgan-gp,GitHub repo for my Tensorflow World hackathon submission
User: harrystuart
wgan-gp,A Tensorflow 2.0 implementation of WGAN-GP
User: henry32144
wgan-gp,Collection of generative models in Tensorflow
User: hwalsuklee
wgan-gp,Improved WGAN in Pytorch
User: jalola
wgan-gp,speech enhancement GAN on waveform/log-power-spectrum data using Improved WGAN
User: jerrygood0703
wgan-gp,Generative Adversarial Networks with TensorFlow2, Keras and Python (Jupyter Notebooks Implementations)
User: kartikgill
Home Page: https://dropsofai.com
wgan-gp,The GAN Book: Train stable Generative Adversarial Networks using TensorFlow2, Keras and Python.
User: kartikgill
wgan-gp,Awesome Generative Adversarial Networks with tensorflow
User: kozistr
wgan-gp,GAN and VAE implementations to generate artificial EEG data to improve motor imagery classification. Data based on BCI Competition IV, datasets 2a. Final project for UCLA's EE C247: Neural Networks and Deep Learning course.
User: krishk97
wgan-gp,[CVPR 2020 Workshop] A PyTorch GAN library that reproduces research results for popular GANs.
User: kwotsin
wgan-gp,Improved Wasserstein GAN (WGAN-GP) application on medical (MRI) images
User: laurahanu
wgan-gp,A Tensorflow implementation of GAN, WGAN and WGAN with gradient penalty.
User: lilianweng
wgan-gp,implementation of several GANs with pytorch
User: lixianghan
Home Page: https://github.com/LixiangHan/GANs-for-1D-Signal
wgan-gp,Improved training of Wasserstein GANs
User: lornatang
wgan-gp,Generative Deep Learning Sessions led by Anugraha Sinha (Machine Learning Tokyo)
Organization: machine-learning-tokyo
Home Page: https://www.meetup.com/Machine-Learning-Tokyo/
wgan-gp,🚀 Variants of GANs most easily implemented as TensorFlow2. GAN, DCGAN, LSGAN, WGAN, WGAN-GP, DRAGAN, ETC...
User: marload
wgan-gp,Implementation of some different variants of GANs by tensorflow, Train the GAN in Google Cloud Colab, DCGAN, WGAN, WGAN-GP, LSGAN, SNGAN, RSGAN, RaSGAN, BEGAN, ACGAN, PGGAN, pix2pix, BigGAN
User: mingtaoguo
wgan-gp,Deep CNN for performing 3D super resolution on CT/MRI scans
User: omagdy
wgan-gp,Chainer implementation of recent GAN variants
Organization: pfnet-research
wgan-gp,Pure tensorflow implementation of progressive growing of GANs
User: preritj
wgan-gp,ProGAN with Standard, WGAN, WGAN-GP, LSGAN, BEGAN, DRAGAN, Conditional GAN, InfoGAN, and Auxiliary Classifier GAN training methods
User: rahulbhalley
Home Page: https://arxiv.org/abs/1710.10196
wgan-gp,ClassicGAN: Generation of Classical Music with PGGAN
User: rick-mccoy
wgan-gp,From scratch, simple and easy-to-understand Pytorch implementation of variants of generative adversarial network (GAN). Implemented variants: Conditional GAN (cGAN), DCGAN, LSGAN. Datasets used MNIST, SVHN, FashionMNIST, CIFAR10, CelebA, LSUN-Bedroom, LSUN-Church.
User: s-chh
wgan-gp,TensorFlow implementations of Wasserstein GAN with Gradient Penalty (WGAN-GP), Least Squares GAN (LSGAN), GANs with the hinge loss.
User: shaohua0116
wgan-gp,Implementation of our paper "Wasserstein Adversarial Transformer for Cloud Workload Prediction"
User: shivaniarbat
wgan-gp,[CVPR 2021: Oral] In this work, we show that high frequency Fourier spectrum decay discrepancies are not inherent characteristics for existing CNN-based generative models.
Organization: sutd-visual-computing-group
Home Page: https://keshik6.github.io/Fourier-Discrepancies-CNN-Detection/
wgan-gp,Keras implementation of "Image Inpainting via Generative Multi-column Convolutional Neural Networks" paper published at NIPS 2018
User: tlatkowski
wgan-gp,Simple Pytorch implementations of most used Generative Adversarial Network (GAN) varieties.
User: wangguanan
wgan-gp,Simple Implementation of many GAN models with PyTorch.
User: yangyangii
wgan-gp,Pytorch implementations of GANs
User: yeonwoosung
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