Generative adversarial networks 101Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.
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Tf Exercise GanTensorflow implementation of different GANs and their comparisions
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Awesome GansAwesome Generative Adversarial Networks with tensorflow
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Ganotebookswgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch
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Pytorch Mnist Celeba Gan DcganPytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets
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PycadlPython package with source code from the course "Creative Applications of Deep Learning w/ TensorFlow"
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cDCGANPyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)
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DCGAN-PytorchA Pytorch implementation of "Deep Convolutional Generative Adversarial Networks"
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PsganPeriodic Spatial Generative Adversarial Networks
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Pytorch GanA minimal implementaion (less than 150 lines of code with visualization) of DCGAN/WGAN in PyTorch with jupyter notebooks
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Wasserstein GanChainer implementation of Wasserstein GAN
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Deep Learning With PythonExample projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.
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Fun-with-MNISTPlaying with MNIST. Machine Learning. Generative Models.
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Pytorch-Basic-GANsSimple Pytorch implementations of most used Generative Adversarial Network (GAN) varieties.
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Generative-ModelRepository for implementation of generative models with Tensorflow 1.x
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GANs-KerasGANs Implementations in Keras
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Tensorflow Mnist Gan DcganTensorflow implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Netwokrs for MNIST dataset.
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Tensorflow DCGANStudy Friendly Implementation of DCGAN in Tensorflow
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Dcgan wgan wgan Gp lsgan sngan rsgan began acgan pggan tensorflowImplementation 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
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Mimicry[CVPR 2020 Workshop] A PyTorch GAN library that reproduces research results for popular GANs.
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Unified Gan TensorflowA Tensorflow implementation of GAN, WGAN and WGAN with gradient penalty.
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Generative ModelsAnnotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
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CatdcganA DCGAN that generate Cat pictures 🐱💻
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Gans In ActionCompanion repository to GANs in Action: Deep learning with Generative Adversarial Networks
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Dcgan TensorflowA Tensorflow implementation of Deep Convolutional Generative Adversarial Networks trained on Fashion-MNIST, CIFAR-10, etc.
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Pix2pixImage-to-image translation with conditional adversarial nets
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Gan VisVisualization of GAN training process
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Pytorch BookPyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch:入门与实战》)
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DeeplearningDeep Learning From Scratch
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Ios Coreml MnistReal-time Number Recognition using Apple's CoreML 2.0 and MNIST -
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Fashion MnistA MNIST-like fashion product database. Benchmark 👇
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PytorchPyTorch tutorials A to Z
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GanspaceDiscovering Interpretable GAN Controls [NeurIPS 2020]
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CaloganGenerative Adversarial Networks for High Energy Physics extended to a multi-layer calorimeter simulation
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Celeba Hq ModifiedModified h5tool.py make user getting celeba-HQ easier
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Sprint ganPrivacy-preserving generative deep neural networks support clinical data sharing
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Gan steerabilityOn the "steerability" of generative adversarial networks
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Capsule GanCode for my Master thesis on "Capsule Architecture as a Discriminator in Generative Adversarial Networks".
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Msg Gan V1MSG-GAN: Multi-Scale Gradients GAN (Architecture inspired from ProGAN but doesn't use layer-wise growing)
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GpndGenerative Probabilistic Novelty Detection with Adversarial Autoencoders
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StarnetStarNet
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Data science blogsA repository to keep track of all the code that I end up writing for my blog posts.
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