Must-Read Papers on Generative Adversarial Networks (GANs) - Crossminds
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Must-Read Papers on Generative Adversarial Networks (GANs)
Generative Adversarial Networks (GANs) are one of the most popular techniques in deep learning. GANs use two neural networks to generate new, synthetic instances of data that can pass for real data. This graph maps the most important papers and their video summaries derived from the original GANs proposed by Ian Goodfellow.
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