A pytorch implementation of pix2pix + BEGAN (Boundary Equilibrium Generative Adversarial Networks)
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Updated
Aug 3, 2019 - HTML
Generative adversarial networks (GAN) are a class of generative machine learning frameworks. A GAN consists of two competing neural networks, often termed the Discriminator network and the Generator network. GANs have been shown to be powerful generative models and are able to successfully generate new data given a large enough training dataset.
A pytorch implementation of pix2pix + BEGAN (Boundary Equilibrium Generative Adversarial Networks)
Python code + notebooks to fully reproduce the results for the blog post "These Bored Apes Do Not Exist" on Medium. Blog post URL: https://medium.com/@nathancooperjones/these-bored-apes-do-not-exist-6bed2c73f02c
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💤🖌️ AI making tiny Bitsy video games. Features an experimental generative structure inspired by GANs and Genetic Algorithms
Utility files for Granular challenge.
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