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Generative Adversarial Networks

Authors :
David Paper
Source :
State-of-the-Art Deep Learning Models in TensorFlow ISBN: 9781484273401
Publication Year :
2021
Publisher :
Apress, 2021.

Abstract

Generative modeling is an unsupervised learning technique that involves automatically discovering and learning the regularities (or patterns) in input data so that a trained model can generate new examples that plausibly could have been drawn from the original dataset. A popular type of generative model is a generative adversarial network. Generative adversarial networks (GANs) are generative models that create new data instances that resemble the training data.

Details

ISBN :
978-1-4842-7340-1
ISBNs :
9781484273401
Database :
OpenAIRE
Journal :
State-of-the-Art Deep Learning Models in TensorFlow ISBN: 9781484273401
Accession number :
edsair.doi...........935223fce6c1f8eff8cb8fcdd8e8e07d
Full Text :
https://doi.org/10.1007/978-1-4842-7341-8_10