Can you explain what Generative Adversarial Networks are?
Generative Adversarial Networks, or GANs, are a class of machine learning frameworks designed to generate new data instances.
How do GANs work?
GANs consist of two neural networks, a generator and a discriminator, that compete against each other to improve their performance.
What are some applications of GANs?
GANs are used in various fields, including image generation, video creation, and even in enhancing image resolution.
Are there any challenges associated with GANs?
Yes, challenges include training instability and mode collapse, where the generator produces limited varieties of outputs.
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