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Rocket enjoyer | Artism haver (pixiv.net/en/users/31349…) | Massive weeb | 3D printing enthusiast | PhD | Postdoc | DMs Open | 🔞: @akuma_1997

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Stopping training for the 128x128 model here, it's gotten good enough to prove the architecture works, now to work on increasing resolution and reducing training time.

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Attempting to find close representations to a target image doesn't seem to go very well, some major features are reflected in the top rated results of each iteration, so maybe I should explore using a more creative search approach

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this culminates in the following 128x128 output:

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Dramatic improvement in generated quality via feature matching

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Testing out a 128x128 to 512x512 upscaler

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4-5 hours of transfer learning from my previous best GAN on a newer dataset

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