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This serves as a log of the approaches I used in exploring Deep Learning in Image Generation. I will discuss the results of the several approaches I have taken, including VAE(Variational Autoencoder), GAN(Generative Adversarial Network), and U-Network(pix2pix). I have tried several methods of each and obtained an understanding of why some of them work and some of them don't.

• Variational Autoencoder
• Generative Adversarial Network
• Combining VAE and GAN
• U-network(pix2pix)