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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
NVlabs denoising-diffusion-gan - GitHub Generative denoising diffusion models typically assume that the denoising distribution can be modeled by a Gaussian distribution This assumption holds only for small denoising steps, which in practice translates to thousands of denoising steps in the synthesis process In our denoising diffusion
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
GitHub - Hzzone DU-GAN: DU-GAN: Generative Adversarial Networks with . . . This repository contains the PyTorch implementation of the paper: DU-GAN: Generative Adversarial Networks with Dual-Domain U-Net Based Discriminators for Low-Dose CT Denoising accepted by IEEE Transactions on Instrumentation Measurement 2021
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
lukemelas pytorch-pretrained-gans - GitHub Pretrained GANs in PyTorch: StyleGAN2, BigGAN, BigBiGAN, SAGAN, SNGAN, SelfCondGAN, and more - lukemelas pytorch-pretrained-gans