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- gan · GitHub Topics · GitHub
Generative adversarial networks (GAN) are a class of generative machine learning frameworks A GAN consists of two competing neural networks, often termed the Discriminator network and the Generator network GANs have been shown to be powerful generative models and are able to successfully generate new data given a large enough training dataset
- GitHub - eriklindernoren PyTorch-GAN: PyTorch implementations of . . .
The key idea of Softmax GAN is to replace the classification loss in the original GAN with a softmax cross-entropy loss in the sample space of one single batch In the adversarial learning of N real training samples and M generated samples, the target of discriminator training is to distribute all the probability mass to the real samples, each
- tensorflow gan: Tooling for GANs in TensorFlow - GitHub
TF-GAN is composed of several parts, which are designed to exist independently: Core : the main infrastructure needed to train a GAN Set up training with any combination of TF-GAN library calls, custom-code, native TF code, and other frameworks
- GitHub - Yangyangii GAN-Tutorial: Simple Implementation of many GAN . . .
Simple Implementation of many GAN models with PyTorch Topics pytorch gan mnist infogan dcgan regularization celeba wgan began wgan-gp infogan-pytorch conditional-gan pytorch-gan gan-implementations vanilla-gan gan-pytorch gan-tutorial stanford-cars cars-dataset began-pytorch
- GitHub - yfeng95 GAN: Resources and Implementations of Generative . . .
GAN before using JS divergence has the problem of non-overlapping, leading to mode collapse and convergence difficulty Use EM distance or Wasserstein-1 distance, so GAN solve the two problems above without particular architecture (like dcgan)
- GitHub - poloclub ganlab: GAN Lab: An Interactive, Visual . . .
GAN Lab is a novel interactive visualization tool for anyone to learn and experiment with Generative Adversarial Networks (GANs), a popular class of complex deep learning models With GAN Lab, you can interactively train GAN models for 2D data distributions and visualize their inner-workings, similar to TensorFlow Playground
- lukemelas pytorch-pretrained-gans - GitHub
Pretrained GANs in PyTorch: StyleGAN2, BigGAN, BigBiGAN, SAGAN, SNGAN, SelfCondGAN, and more - lukemelas pytorch-pretrained-gans
- generative-adversarial-network · GitHub Topics · GitHub
Generative adversarial networks (GAN) are a class of generative machine learning frameworks A GAN consists of two competing neural networks, often termed the Discriminator network and the Generator network GANs have been shown to be powerful generative models and are able to successfully generate new data given a large enough training dataset
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