Generative Adversarial Networks (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
GAN - Architecture
---cognitive-computing---machine-intelligence/ai---subfields/machine-learning-(ml)---pattern-recognition/ml---models/artificial-neural-networks-(ann)/ann---architectures/generative-adversarial-networks-(gan)/gans-architecture.png)
GAN - Subpages
- GAN vs VAE vs Flow-Based Model vs Diffusion Model
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