A generative adversarial network (GAN) is a class of machine learning frameworks and a prominent framework for approaching generative AI. The concept...

The Wasserstein Generative Adversarial Network (WGAN) is a variant of generative adversarial network (GAN) proposed in 2017 that aims to "improve the stability...

variational autoencoder and generative adversarial network produced the first practical deep neural networks capable of learning generative models, as opposed...

2014, the adversarial network principle was used in a generative adversarial network (GAN) by Ian Goodfellow et al. Here the adversarial network (discriminator)...

potential samples of input variables. Generative adversarial networks are examples of this class of generative models, and are judged primarily by the...

nor used gradient descent." In 2014, this adversarial principle was used in a generative adversarial network (GAN) by Ian Goodfellow et al. Here the environmental...

contrast, many alternative generative modeling methods such as variational autoencoder (VAE) and generative adversarial network do not explicitly represent...

StyleGAN is a generative adversarial network (GAN) introduced by Nvidia researchers in December 2018, and made source available in February 2019. StyleGAN...

to the field of deep learning including the invention of the generative adversarial network (GAN). Goodfellow co-wrote, as the first author, the textbook...

conditional generative model for existing information from text can be done by variational autoencoder and generative adversarial network (GAN). There...

quantize a feature representation layer in the discriminator of Generative adversarial networks. The feature quantization (FQ) technique performs implicit...

not seem to apply in the adversarial context. Pattern recognition Fawkes (image cloaking software) Generative adversarial network Kianpour, Mazaher; Wen...

Edmond de Belamy is a generative adversarial network (GAN) portrait painting constructed in 2018 by Paris-based arts-collective Obvious. Printed on canvas...

used to assess the quality of images created by a generative model, like a generative adversarial network (GAN). Unlike the earlier inception score (IS)...

2020). "Retrospective Motion Correction in Multishot MRI using Generative Adversarial Network". Scientific Reports. 10 (1): 4786. arXiv:1902.07430. Bibcode:2020NatSR...

the 2010s. He also introduced principles of meta-learning, generative adversarial networks and linear transformers, all of which are widespread in modern...

extremely successful classical Generative adversarial network(GAN), dissipative quantum generative adversarial network (DQGAN) is introduced for unsupervised...

at Université de Montréal developed the generative adversarial network (GAN), a type of deep neural network capable of learning to mimic the statistical...

"Enhanced Deep Residual Networks for Single Image Super-Resolution". arXiv:1707.02921 [cs.CV]. "Generative Adversarial Network and Super Resolution GAN(SRGAN)"...

figure's voice being used against them. This method uses a generative adversarial network (GAN), a deep machine learning technique where two machine learning...

and generative adversarial networks to obtain hybrid models. Autoencoder Artificial neural network Deep learning Generative adversarial network Representation...

a generative adversarial network (GAN) by Ian Goodfellow et al. Here the environmental reaction is 1 or 0 depending on whether the first network's output...

assess the quality of images created by a generative image model such as a generative adversarial network (GAN). The score is calculated based on the...

source - Zanini, et al. noted that it is possible to use a generative adversarial network (in particular, a DCGAN) to perform style transfer in order...

systems Generative adversarial network – Deep learning method Generative art – Art created by a set of rules, often using computers Generative artificial...

Retrieved 25 August 2017. "Yet Another Text Captcha Solver: A Generative Adversarial Network Based Approach" (PDF). 25th ACM Conference on Computer and Communications...

algorithms and artificial neural networks such as variational autoencoders (VAEs) and generative adversarial networks (GANs). In turn the field of image...

compete with techniques such as variational autoencoders (VAEs), generative adversarial networks (GANs) or normalizing flows. Joint energy-based models (JEM)...

Synthetic media as a field has grown rapidly since the creation of generative adversarial networks, primarily through the rise of deepfakes as well as music synthesis...

same as vector quantized variational autoencoder (VQVAE) plus generative adversarial network (GAN). After such a ViT-VQGAN is trained, it can be used to...