Generative adversarial network
id:
generative-adversarial-network-181-3565067
title:
Generative adversarial network
text:
A generative adversarial network (GAN) is a class of machine learning frameworks and a prominent framework for approaching generative AI. The concept was initially developed by Ian Goodfellow and his colleagues in June 2014. In a GAN, two neural networks contest with each other in the form of a zero-sum game, where one agent's gain is another agent's loss. Given a training set, this technique learns to generate new data with the same statistics as the training set. For example, a GAN trained on
brand slug:
wiki
category slug:
encyclopedia
description:
Deep learning method
original url:
https://en.wikipedia.org/wiki/Generative_adversarial_network
date created:
2016-04-07T13:45:58Z
date modified:
2024-09-06T01:01:52Z
main entity:
{"identifier":"Q25104379","url":"https://www.wikidata.org/entity/Q25104379"}
image:
{"content_url":"https://upload.wikimedia.org/wikipedia/commons/8/83/Generative_adversarial_network.svg","width":176,"height":205}
fields total:
13
integrity:
16